Drawing of various file cabinets opened to symbolize a lot of data.

Tembo capitalizes on the database boom and lands new cash to expand

Drawing of various file cabinets opened to symbolize a lot of data.

Image Credits: 3alexd / Getty Images

As the demand for AI grows, so, too, does the demand for expertise in maintaining databases — a critical part in any AI pipeline. Databases store the information used to train, run and fine-tune AI systems, and it’s been shown that good data management can smooth the pathway to AI adoption in an enterprise.

One of the vendors to benefit from the database boom is Tembo, a startup creating a platform that lets developers deploy different flavors of Postgres, the open source database system, to cloud and local environments. Tembo on Monday announced that it raised $14 million in a funding round led by GreatPoint Ventures with participation from Venrock, Grand Ventures, Wireframe Ventures, Defined VC and Cintrifuse Capital.

“We’re harnessing the power of Postgres for everyone to use,” Tembo founder and CEO Ry Walker told TechCrunch. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

Walker studied computer science at the University of Cincinnati before dropping out to build a web agency, Sharkbytes, in the ’90s. After selling his first company, Walker started Differential, a venture studio, out of which spun Astronomer, an open source data engineering pipeline that Walker co-founded.

It was shortly after the launch of Astronomer that Walker said he realized his passion for early-stage ventures. So he founded Tembo. “After building Astronomer and working on open source passion projects, I realized our model at Astronomer could be applied to the database industry with even more impact,” he said.

Tembo provides a managed, metered software-as-a-service Postgres service as well as self-hosted software to set up and orchestrate Postgres databases. Customers can spin up databases with features like auto-scaling and soon auto-tuning for self-maintenancing.

Recently, Tembo launched Machine Learning Stack, which allows devs to build and deploy AI models — including the open generative AI models that Tembo provides as a service — leveraging workflows alongside their databases.

“The astronomical increase in data has caused a massive data sprawl that is inefficient and extremely expensive,” Walker said. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

With $20 million in capital and a team of about 25 people, Cincinnati-based Tembo plans to focus on product development, hiring and advertising, Walker said. The challenge will be continuing to beat back rivals, including Postgres creator Mike Stonebraker’s new startup, DBOS. But Walker says that Tembo’s up to it.

“We’re reaching a critical inflection point to help enterprises with their strategy by leveraging Postgres for all of their growing data capture and storing needs,” Walker said. “The global database market is growing 15% year-over-year, expected to be $200 billion by 2027. This is just the tip of the iceberg over the next decade. Our goal is just as ambitious as the opportunity; we’re harnessing the power of Postgres for everyone to use.”

TigerBeetle is building database software optimized for financial transactions

Image Credits: Bortonia (opens in a new window) / Getty Images

After doing some consulting for Microsoft to develop protections against zero-day exploits, software engineer Joran Dirk Greef worked with Coil, a web monetization startup in San Francisco, to help build its payments infrastructure. At the time, Coil was using a traditional database to store and process transactions. But Greef had the insight that a specialized database could prove to be much more nimble — and powerful.

The idea morphed into a skunkworks project at Coil, and Greef became a staff engineer working full-time on a new database design called TigerBeetle. Two years into the project, after customers started requesting enterprise support for the database, Greef spun out TigerBeetle as a startup.

TigerBeetle’s open source database is engineered for financial online transaction processing, Greef says, capable of handling more than 8,000 debit and credit card transactions in a single query. One query for 8,000 transactions might not sound like a lot. But most general-purpose databases would require 1 to 10 queries per transaction. And more queries translates to more latency — especially if the database is hosted on a remote server somewhere.

“TigerBeetle is a financial transactions database that provides debit/credit primitives out of the box and enforces financial consistency in the database without requiring a developer to cobble together a system of record from scratch,” Greef said.

“TigerBeetle is ideal for use cases where you need to count anything of value — not necessarily money, but including money — moving from one person or place to another,” Greef said. A common application is an internal ledger for a company like Transferwise, he added, which has to keep track of lots of money moving between accounts.

Spinning out TigerBeetle was a wise decision in hindsight. TigerBeetle recently closed a $24 million Series A round led by Spark Capital’s Natalie Vais with participation from Amplify Partners and Coil, bringing its total raised to more than $30 million. A source familiar with the matter tells TechCrunch that TigerBeetle is valued at around $100 million post-money.

“We had planned to raise later in the year,” Greef said. “However, after a surge in community growth at the beginning of 2024, and growing commercial interest, we decided to bring the raise forward to invest in engineering, go-to-market and TigerBeetle’s cloud platform, which is under development.”

TigerBeetle, which only has eight employees at present and plans to double the size of its team by 2025, provides its database technology in the form of a managed service. Greef claims that TigerBeetle has had paying customers “since day one” and that the TigerBeetle community — folks using or contributing to the open source release — has grown over 200% year-over-year.

Vais told TechCrunch that TigerBeetle is one of the more exciting database projects that she’s seen recently.

“TigerBeetle rethinks every component from the ground up to handle modern transactional workloads,” she said. “In a world where everything is becoming more online and more transactional, there’s a huge opportunity for TigerBeetle to become a foundational piece of infrastructure for modern systems of record.”

TigerBeetle’s managed service is currently available by invitation only, and the database reached its first production release just in March. But Greef says that growth — in particular acquiring new customers — will be the focus for the foreseeable future.

“TigerBeetle’s use cases extend beyond fintech,” he continued. “Think usage-based billing with real-time spend caps, gaming live ops and energy smart meters, as well as instant payments, core banking, brokering, inventory, shopping carts, trucking and shipping, warehousing, crowdfunding, voting and reservation systems.”

Database startup Neon nabs a Microsoft investment

illustration of large bank of nlue filing cabinets with several drawers open

Image Credits: sorbetto (opens in a new window) / Getty Images

In a sign that big tech companies are ready and willing to shell out cash for database tech, Neon, a startup building an open source alternative to AWS Aurora Postgres, on Wednesday announced that Microsoft’s venture arm M12 led a $25 million strategic investment in its business.

The capital will go toward R&D, Neon co-founder and CEO Nikita Shamgunov says, fueling Neon’s expansion into Microsoft Azure and the development of new database capabilities to support both existing and new customers.

“We’re not looking to raise — this is not a new round,” Shamgunov told TechCrunch. “We are well-capitalized with more than $100 million in funding. But this is Microsoft. We couldn’t pass up the opportunity to strengthen Neon’s relationship with Microsoft and Azure, their role in the future of developer tools is only growing.”

Added M12 managing partner Andrew Smyth: “Postgres is quickly becoming the database of choice for developers and we are investing heavily in that ecosystem. Neon is a leading Postgres platform and this strategic investment emphasizes our commitment to deeply integrate Neon into Azure.”

Shamgunov started Neon in 2021 alongside software engineers Heikki Linnakangas and Stas Kelvich. Prior to Neon, Shamgunov founded MemSQL, now SingleStore, where he was CTO and then became CEO.

While at SingleStore, Shamgunov says that he noticed just how much Postgres, the relational database management system, was out there in the world, and sensed an opportunity to build an alternative to Aurora (if only to counter an AWS monopoly).

Postgres has grown massively in popularity over the past few years. According to a 2023 Stack Overflow survey, just over 45% of developers said they use Postgres — ahead of MySQL and SQLite, the previous top choices.

“Neon is a Postgres database company,” Shamgunov said. “We take Postgres and tease apart the internal components into a platform designed to help everyone from individual developers to large enterprises build applications.”

Neon’s managed cloud-based database platform, which offers a free tier as well as paid plans with usage-based pricing, allows developers to clone databases for development environments and preview changes before they go to production. The platform scales up processor, memory and storage with usage automatically, minimizing the need for customers to do so themselves.

“Engineering teams at scale-ups and enterprise typically adopt Neon for one of two reasons: Using Neon to manage fleets of Postgres without overhead and increasing development velocity,” Shamgunov said. “Migrating a production database is risky, so scale-ups that want to ship faster will move only non-production work to Neon to take advantage of the developer productivity increases that come from Neon’s database branching workflow.”

Neon has benefited from the generative AI boom, which is fueling the demand for databases to power AI apps. Shamgunov says that hundreds of thousands of developers are using the company’s free tier and that thousands of startups and small- and medium-sized businesses are paying for Neon’s premium services.

“Today, more than 3,000 projects are created on Neon daily,” Shamgunov said. “Technology spending is constantly evolving, but every business, every software-as-a-service product, every application, every mobile app and every AI tool needs a database. Neon sees an acceleration in growth as software — and now AI — continues to eat the world.”

With $130.6 million total in the bank, Neon now has “many years” of runway, Shamgunov says. The San Francisco-based company plans to grow its 100-person workforce to 120 by the end of the year, investing predominantly in engineering.

Abstract Ventures, General Catalyst, Menlo Ventures and Notable Capital also invested in the strategic round announced today.

illustration of large bank of nlue filing cabinets with several drawers open

Database startup Neon nabs a Microsoft investment

illustration of large bank of nlue filing cabinets with several drawers open

Image Credits: Getty Images

In a sign that big tech companies are ready and willing to shell out cash for database tech, Neon, a startup building an open source alternative to AWS Aurora Postgres, on Wednesday announced that Microsoft’s venture arm M12 led a $25 million strategic investment in its business.

The capital will go toward R&D, Neon co-founder and CEO Nikita Shamgunov says, fueling Neon’s expansion into Microsoft Azure and the development of new database capabilities to support both existing and new customers.

“We’re not looking to raise — this is not a new round,” Shamgunov told TechCrunch. “We are well-capitalized with more than $100 million in funding. But this is Microsoft. We couldn’t pass up the opportunity to strengthen Neon’s relationship with Microsoft and Azure, their role in the future of developer tools is only growing.”

Added M12 manager partner Andrew Smyth: “Postgres is quickly becoming the database of choice for developers and we are investing heavily in that ecosystem. Neon is a leading Postgres platform and this strategic investment emphasizes our commitment to deeply integrate Neon into Azure.”

Shamgunov started Neon in 2021 alongside software engineers Heikki Linnakangas and Stas Kelvich. Prior to Neon, Shamgunov founded MemSQL, now SingleStore, where he was CTO and then became CEO.

While at SingleStore, Shamgunov says that he noticed just how much Postgres, the relational database management system, was out there in the world, and sensed an opportunity to build an alternative to Aurora (if only to counter an AWS monopoly).

Postgres has grown massively in popularity over the past few years. According to a 2023 Stack Overflow survey, just over 45% of developers said they use Postgres — ahead of MySQL and SQLite, the previous top choices.

“Neon is a Postgres database company,” Shamgunov said. “We take Postgres and tease apart the internal components into a platform designed to help everyone from individual developers to large enterprises build applications.”

Neon’s managed cloud-based database platform, which offers a free tier as well as paid plans with usage-based pricing, allows developers to clone databases for development environments and previewing changes before they go to production. The platform scales up processor, memory and storage with usage automatically, minimizing the need for customers to do so themselves.

“Engineering teams at scale-ups and enterprise typically adopt Neon for one of two reasons: Using Neon to manage fleets of Postgres without overhead and increasing development velocity,” Shamgunov said. “Migrating a production database is risky, so scale-ups that want to ship faster will move only non-production work to Neon to take advantage of the developer productivity increases that come from Neon’s database branching workflow.”

Neon has benefited from the generative AI boom, which is fueling the demand for databases to power AI apps. Shamgunov says that hundreds of thousands of developers are using the company’s free tier and that thousands of startups and small- and medium-sized businesses are paying for Neon’s premium services.

“Today, more than 3,000 projects are created on Neon daily,” Shamgunov said. “Technology spending is constantly evolving, but every business, every software-as-a-service product, every application, every mobile app and every AI tool needs a database. Neon sees an acceleration in growth as software — and now AI — continues to eat the world.”

With $130.6 million total in the bank, Neon now has “many years” of runway, Shamgunov says. The San Francisco-based company plans to grow its 100-person workforce to 120 by the end of the year, investing predominantly in engineering.

Abstract Ventures, General Catalyst, Menlo Ventures and Notable Capital also invested in the strategic round announced today.

Google Cloud expands its database portfolio with new AI capabilities

Image Credits: Krisztian Bocsi/Bloomberg / Getty Images

Google is hosting a version of its Cloud Next conference in Tokyo this week, and it’s putting the focus squarely on tweaking its databases for AI workloads (because at this point in 2024, AI is the only thing these major tech companies want to talk about). These include updates to its Spanner SQL database, which now features graph and vector search support, as well as extended full-text search capabilities.

This wouldn’t be a Google announcement without some Gemini-powered features. These include Gemini in BigQuery and Looker to help users with data engineering and analysis, as well as governance and security tasks.

Google argues that while the vast majority of enterprises think that generative AI will be critical to the success of their business, they also know that much of their data remains unmanaged, leaving it outside of the scope of their analytics and AI initiatives.

“They have to really get out of all of their existing data silos and data islands, and get to a consolidated multimodal data platform, spanning structured and unstructured data — [because] GenAI is terrific at analyzing unstructured data — and combining data at rest with their data movement, so real-time data and data at rest processing,” explained Gerrit Kazmeier, Google’s VP and GM for database, Data Analytics and Looker. Activating this enterprise data flow, he argued, is what a lot of these new features are all about.

Spanner gets graph and vector capabilities

Spanner powers most of Google’s own products like Search, Gmail and YouTube and its customer list includes the likes of Home Depot, Uber, Walmart and others. And while Spanner can handle a massive volume of data, vector and graph databases are a necessity to bring enterprise data into GenAI applications and enrich existing foundation models.

“What we’re thinking about is what would it really take for us to take Spanner’s availability, scale, relational model, and really expand that to be the best data platform for operational GenAI apps,” said Andi Gutmans, Google’s VP and GM for databases. Like so many database vendors, the first step here for Google is adding graph capabilities to Spanner, using the emerging GraphQL standard. Enterprises can then use this graph to augment their GenAI applications — and the foundation models that power them — using Retrieval Augmented Generation (RAG), which is currently the de facto standard for this use case.

Also new in Spanner are full-text search and vector search, with the vector search capabilities backed by Google’s ScaNN algorithm. “With Spanner Graph, full-text search and vector search, we have evolved Spanner from not only being the most available, globally consistent and scalable database, to a multi-model database with intelligent capabilities that seamlessly interoperate to enable you to deliver a new class of AI-enabled applications,” Google says.

In addition to these AI-centric updates, Spanner is getting a new, optional pricing structure. Dubbed “Spanner editions,” the idea here is to offer a tier-based pricing model that offers them more flexibility. Currently, Google Cloud customers had to choose between a single-region offering and a multi-region version, which also offered a bundle of additional features like replication.

Bigtable goes SQL

Google also on Thursday announced a major update to Bigtable, Google’s NoSQL database for unstructured data and latency-sensitive workloads. Bigtable now features SQL support (or more precisely, support for GoogleSQL, the company’s own SQL dialect), making it significantly easier for virtually any developer to use the service.

Previously, developers had to use the Bigtable API to query their databases. Currently, Bigtable supports roughly 100 SQL functions.

Oracle on Google Cloud

For the Oracle database fans out there, Google will now allow them to host their Oracle Exadata and Autonomous database services right in the Google Cloud data centers — and they can link their applications between Google Cloud and the Oracle Cloud. For Google, that means more workloads in its cloud and for Oracle, at least, it means these users are still paying their licensing fees, even if they aren’t using the Oracle cloud.

Also new in Google Cloud is support for open-source Apache Spark and Kafka for data streaming and processing, as well as real-time streaming from Analytics Hub (Google’s service for securely sharing data between organizations).

Tembo capitalizes on the database boom and lands new cash to expand

Drawing of various file cabinets opened to symbolize a lot of data.

Image Credits: 3alexd / Getty Images

As the demand for AI grows, so, too, does the demand for expertise in maintaining databases — a critical part in any AI pipeline. Databases store the information used to train, run and fine-tune AI systems, and it’s been shown that good data management can smooth the pathway to AI adoption in an enterprise.

One of the vendors to benefit from the database boom is Tembo, a startup creating a platform that lets developers deploy different flavors of Postgres, the open source database system, to cloud and local environments. Tembo on Monday announced that it raised $14 million in a funding round led by GreatPoint Ventures with participation from Venrock, Grand Ventures, Wireframe Ventures, Defined VC and Cintrifuse Capital.

“We’re harnessing the power of Postgres for everyone to use,” Tembo founder and CEO Ry Walker told TechCrunch. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

Walker studied computer science at the University of Cincinnati before dropping out to build a web agency, Sharkbytes, in the ’90s. After selling his first company, Walker started Differential, a venture studio, out of which spun Astronomer, an open source data engineering pipeline that Walker co-founded.

It was shortly after the launch of Astronomer that Walker said he realized his passion for early-stage ventures. So he founded Tembo. “After building Astronomer and working on open source passion projects, I realized our model at Astronomer could be applied to the database industry with even more impact,” he said.

Tembo provides a managed, metered software-as-a-service Postgres service as well as self-hosted software to set up and orchestrate Postgres databases. Customers can spin up databases with features like auto-scaling and soon auto-tuning for self-maintenancing.

Recently, Tembo launched Machine Learning Stack, which allows devs to build and deploy AI models — including the open generative AI models that Tembo provides as a service — leveraging workflows alongside their databases.

“The astronomical increase in data has caused a massive data sprawl that is inefficient and extremely expensive,” Walker said. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

With $20 million in capital and a team of about 25 people, Cincinnati-based Tembo plans to focus on product development, hiring and advertising, Walker said. The challenge will be continuing to beat back rivals, including Postgres creator Mike Stonebraker’s new startup, DBOS. But Walker says that Tembo’s up to it.

“We’re reaching a critical inflection point to help enterprises with their strategy by leveraging Postgres for all of their growing data capture and storing needs,” Walker said. “The global database market is growing 15% year-over-year, expected to be $200 billion by 2027. This is just the tip of the iceberg over the next decade. Our goal is just as ambitious as the opportunity; we’re harnessing the power of Postgres for everyone to use.”

TigerBeetle is building database software optimized for financial transactions

Image Credits: Bortonia (opens in a new window) / Getty Images

After doing some consulting for Microsoft to develop protections against zero-day exploits, software engineer Joran Dirk Greef worked with Coil, a web monetization startup in San Francisco, to help build its payments infrastructure. At the time, Coil was using a traditional database to store and process transactions. But Greef had the insight that a specialized database could prove to be much more nimble — and powerful.

The idea morphed into a skunkworks project at Coil, and Greef became a staff engineer working full-time on a new database design called TigerBeetle. Two years into the project, after customers started requesting enterprise support for the database, Greef spun out TigerBeetle as a startup.

TigerBeetle’s open source database is engineered for financial online transaction processing, Greef says, capable of handling more than 8,000 debit and credit card transactions in a single query. One query for 8,000 transactions might not sound like a lot. But most general-purpose databases would require 1 to 10 queries per transaction. And more queries translates to more latency — especially if the database is hosted on a remote server somewhere.

“TigerBeetle is a financial transactions database that provides debit/credit primitives out of the box and enforces financial consistency in the database without requiring a developer to cobble together a system of record from scratch,” Greef said.

“TigerBeetle is ideal for use cases where you need to count anything of value — not necessarily money, but including money — moving from one person or place to another,” Greef said. A common application is an internal ledger for a company like Transferwise, he added, which has to keep track of lots of money moving between accounts.

Spinning out TigerBeetle was a wise decision in hindsight. TigerBeetle recently closed a $24 million Series A round led by Spark Capital’s Natalie Vais with participation from Amplify Partners and Coil, bringing its total raised to more than $30 million. A source familiar with the matter tells TechCrunch that TigerBeetle is valued at around $100 million post-money.

“We had planned to raise later in the year,” Greef said. “However, after a surge in community growth at the beginning of 2024, and growing commercial interest, we decided to bring the raise forward to invest in engineering, go-to-market and TigerBeetle’s cloud platform, which is under development.”

TigerBeetle, which only has eight employees at present and plans to double the size of its team by 2025, provides its database technology in the form of a managed service. Greef claims that TigerBeetle has had paying customers “since day one” and that the TigerBeetle community — folks using or contributing to the open source release — has grown over 200% year-over-year.

Vais told TechCrunch that TigerBeetle is one of the more exciting database projects that she’s seen recently.

“TigerBeetle rethinks every component from the ground up to handle modern transactional workloads,” she said. “In a world where everything is becoming more online and more transactional, there’s a huge opportunity for TigerBeetle to become a foundational piece of infrastructure for modern systems of record.”

TigerBeetle’s managed service is currently available by invitation only, and the database reached its first production release just in March. But Greef says that growth — in particular acquiring new customers — will be the focus for the foreseeable future.

“TigerBeetle’s use cases extend beyond fintech,” he continued. “Think usage-based billing with real-time spend caps, gaming live ops and energy smart meters, as well as instant payments, core banking, brokering, inventory, shopping carts, trucking and shipping, warehousing, crowdfunding, voting and reservation systems.”

Tembo capitalizes on the database boom and lands new cash to expand

Drawing of various file cabinets opened to symbolize a lot of data.

Image Credits: 3alexd / Getty Images

As the demand for AI grows, so, too, does the demand for expertise in maintaining databases — a critical part in any AI pipeline. Databases store the information used to train, run and fine-tune AI systems, and it’s been shown that good data management can smooth the pathway to AI adoption in an enterprise.

One of the vendors to benefit from the database boom is Tembo, a startup creating a platform that lets developers deploy different flavors of Postgres, the open source database system, to cloud and local environments. Tembo on Monday announced that it raised $14 million in a funding round led by GreatPoint Ventures with participation from Venrock, Grand Ventures, Wireframe Ventures, Defined VC and Cintrifuse Capital.

“We’re harnessing the power of Postgres for everyone to use,” Tembo founder and CEO Ry Walker told TechCrunch. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

Walker studied computer science at the University of Cincinnati before dropping out to build a web agency, Sharkbytes, in the ’90s. After selling his first company, Walker started Differential, a venture studio, out of which spun Astronomer, an open source data engineering pipeline that Walker co-founded.

It was shortly after the launch of Astronomer that Walker said he realized his passion for early-stage ventures. So he founded Tembo. “After building Astronomer and working on open source passion projects, I realized our model at Astronomer could be applied to the database industry with even more impact,” he said.

Tembo provides a managed, metered software-as-a-service Postgres service as well as self-hosted software to set up and orchestrate Postgres databases. Customers can spin up databases with features like auto-scaling and soon auto-tuning for self-maintenancing.

Recently, Tembo launched Machine Learning Stack, which allows devs to build and deploy AI models — including the open generative AI models that Tembo provides as a service — leveraging workflows alongside their databases.

“The astronomical increase in data has caused a massive data sprawl that is inefficient and extremely expensive,” Walker said. “With Tembo, enterprises can cut costs by minimizing the number of databases and increase efficiency by enabling less complex data pipelines.”

With $20 million in capital and a team of about 25 people, Cincinnati-based Tembo plans to focus on product development, hiring and advertising, Walker said. The challenge will be continuing to beat back rivals, including Postgres creator Mike Stonebraker’s new startup, DBOS. But Walker says that Tembo’s up to it.

“We’re reaching a critical inflection point to help enterprises with their strategy by leveraging Postgres for all of their growing data capture and storing needs,” Walker said. “The global database market is growing 15% year-over-year, expected to be $200 billion by 2027. This is just the tip of the iceberg over the next decade. Our goal is just as ambitious as the opportunity; we’re harnessing the power of Postgres for everyone to use.”

arrow sign made by pine cones

Pinecone's vector database gets a new serverless architecture

arrow sign made by pine cones

Image Credits: D-BASE / Getty Images

For a long time, vector databases were a bit of a niche product, but because they are uniquely suited to provide context and long-term memory to large language models, everybody in the database space is now seemingly trying to bolt vector search onto their existing products as fast as possible. Meanwhile, dedicated services like Pinecone, which was founded by the team behind Amazon SageMaker, are leading the charge, with Pinecone raising a total of $138 million since it as founded in 2019. Today, Pinecone is launching Pinecone Serverless, a new and significantly enhanced serverless architecture to power its service.

Pinecone Serverless now separates reads, writes and storage, which should reduce costs for users. Indeed, Pinecone argues that its new architecture can offer a 10x to 100x cost reduction. The new architecture now supports vector clustering on top of blob storage. This results in lower latencies and the ability for Pinecone Serverless to support massive data sizes. Likewise, Pinecone Serverless introduces new indexing and retrieval algorithms to enable fast vector search across this blob storage. The service now also offers a multi-tenant compute layer.

“Since it is truly serverless, it completely eliminates the need for developers to provision or manage infrastructure and allows them to build GenAI applications more easily and bring them to market much faster,” the company explains in its announcement. “As a result, developers with use cases of any size can build more reliable, effective, and impactful GenAI applications with any LLM of their choice, leading to an imminent wave of incredible GenAI applications reaching the market.”

From the outset, Pinecone Serverless will offer integrations with several other AI and back-end services, including Anthropic, Anyscale, Cohere, Confluent, LangChain, Pulumi and Vercel. “Vercel’s mission is to help the world ship the best products, and in the age of GenAI that requires Pinecone as the vector database component,” said Guillermo Rauch, CEO and founder of Vercel. “That’s why we are announcing that all Vercel users can now add Pinecone Serverless to their applications in just a few clicks, with more exciting capabilities to come.”

Pinecone drops $100M investment on $750M valuation, as vector database demand grows

arrow sign made by pine cones

Pinecone's vector database gets a new serverless architecture

arrow sign made by pine cones

Image Credits: D-BASE / Getty Images

For a long time, vector databases were a bit of a niche product, but because they are uniquely suited to provide context and long-term memory to large language models, everybody in the database space is now seemingly trying to bolt vector search onto their existing products as fast as possible. Meanwhile, dedicated services like Pinecone, which was founded by the team behind Amazon SageMaker, are leading the charge, with Pinecone raising a total of $138 million since it as founded in 2019. Today, Pinecone is launching Pinecone Serverless, a new and significantly enhanced serverless architecture to power its service.

Pinecone Serverless now separates reads, writes and storage, which should reduce costs for users. Indeed, Pinecone argues that its new architecture can offer a 10x to 100x cost reduction. The new architecture now supports vector clustering on top of blob storage. This results in lower latencies and the ability for Pinecone Serverless to support massive data sizes. Likewise, Pinecone Serverless introduces new indexing and retrieval algorithms to enable fast vector search across this blob storage. The service now also offers a multi-tenant compute layer.

“Since it is truly serverless, it completely eliminates the need for developers to provision or manage infrastructure and allows them to build GenAI applications more easily and bring them to market much faster,” the company explains in its announcement. “As a result, developers with use cases of any size can build more reliable, effective, and impactful GenAI applications with any LLM of their choice, leading to an imminent wave of incredible GenAI applications reaching the market.”

From the outset, Pinecone Serverless will offer integrations with several other AI and back-end services, including Anthropic, Anyscale, Cohere, Confluent, LangChain, Pulumi and Vercel. “Vercel’s mission is to help the world ship the best products, and in the age of GenAI that requires Pinecone as the vector database component,” said Guillermo Rauch, CEO and founder of Vercel. “That’s why we are announcing that all Vercel users can now add Pinecone Serverless to their applications in just a few clicks, with more exciting capabilities to come.”

Pinecone drops $100M investment on $750M valuation, as vector database demand grows