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DataStax
DataStax
DataStax
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DataStax, Inc. is a real-time data for AI company based in Santa Clara, California.[3] Its product Astra DB is a cloud database-as-a-service based on Apache Cassandra. DataStax also offers DataStax Enterprise (DSE), an on-premises database built on Apache Cassandra, and Astra Streaming, a messaging and event streaming cloud service based on Apache Pulsar. As of June 2022, the company has roughly 800 customers distributed in over 50 countries.[4][5][2]

Key Information

History

[edit]

DataStax was built on the open source NoSQL database Apache Cassandra. Cassandra was initially developed internally at Facebook to handle large data sets across multiple servers,[6] and was released as an Apache open source project in 2008.[7] In 2010, Jonathan Ellis and Matt Pfeil left Rackspace, where they had worked with Cassandra, to launch Riptano in Austin, Texas.[6][8] Ellis and Pfeil later renamed the company DataStax, and moved its headquarters to Santa Clara, California.[3][9]

The company went on to create its own enterprise version of Cassandra, a NoSQL database called DataStax Enterprise (DSE).[6]

In 2019, Chet Kapoor was named the company's new CEO, taking over from Billy Bosworth.[10]

Original logo

In May 2020, DataStax released Astra DB, a DBaaS for Cassandra applications.[11] In November 2020, DataStax released K8ssandra, an open source distribution of Cassandra on Kubernetes.[12] In December 2020, DataStax released Stargate, an open source data API gateway.[13]

After acquiring streaming event vendor Kesque in January 2021,[14] the company launched Luna Streaming, a data streaming platform for Apache Pulsar.[15] DataStax then rebuilt the Kesque technology into Astra Streaming.[16] The Astra Streaming cloud service became generally available on June 29, 2022.[17] With the release, the company added API-level support for messaging tools Apache Kafka, RabbitMQ and Java Message Service, in addition to Apache Pulsar.[18][19] Astra Streaming can connect to a larger data platform by utilizing DataStax's Astra DB cloud service.[18]

Starting in 2023, DataStax began incorporating artificial intelligence and machine learning into its platform.[20] In January 2023, the company acquired Kaskada, developer of a platform that helps organizations use data for AI applications.[21] DataStax made the formerly proprietary Kaskada technology open source, and integrated it into its Luna ML service, which was launched on May 4, 2023.[22] With the acquisition, former Kaskada CEO Davor Bonaci was named DataStax chief technology officer and executive vice president.[22]

On May 24, 2023, DataStax announced that it would be partnering with ThirdAI to bring large language models to DSE and AstraDB, to help developers develop generative AI applications.[23]

In June 2023, the company announced the development of a GPT-based schema translator in its Astra Streaming cloud service. The Astra Streaming GPT Schema Translator uses generative AI to automatically generate schema mappings, to enable data integration and interoperability between multiple systems and data sources.[24]

On July 18, 2023, the company announced a partnership with Google to make semantic search available in its Astra DB cloud database for developers building generative AI applications.[20]

On September 13, 2023, DataStax launched the LangStream open source project, which works with Astra DB and supports vector databases including Milvus and Pinecone. LangStream enables developers to better work with streaming data sources, using Apache Kafka technology and generative AI to help build event-driven architectures.[25]

In November 2023, DataStax announced RAGStack, a simplified commercial offering for RAG (retrieval-augmented generation) based on LangChain and Astra DB vector search.[26]

On February 25, 2025, IBM announced its intention to acquire DataStax.[27][28]

On May 28, 2025, IBM announced that it had officially acquired DataStax.[29]

Products

[edit]

Astra DB

[edit]

Astra DB is available on cloud services such as Microsoft Azure, Amazon Web Services, and Google Cloud Platform.[30] In February 2021, DataStax announced the serverless version of Astra DB, offering developers pay-as-you-go data.[31]

In March 2022, DataStax introduced new change data capture (CDC) capabilities to its Astra DB cloud service. Astra DB CDC is powered by Apache Pulsar, which allows developers to manage operational and streaming data in one place.[32] DataStax leads the open-source Starlight, which provides a compatibility layer for different protocols on top of Apache Pulsar.[18]

On February 8, 2023, DataStax launched Astra Block, a cloud-based service based on the Ethereum blockchain to support building Web3 applications, available as part of Astra DB. Astra Block can be used by developers to stream enhanced data from the Ethereum blockchain to build or scale Web3 experiences on Astra DB.[33]

Astra DB supports open source LangChain technology, making it easier for developers to create generative AI applications.[20]

DSE

[edit]

Version 1.0 of the DataStax Enterprise (DSE), released in October 2011, was the first commercial distribution of the Cassandra database, designed to provide real-time application performance and heavy analytics on the same physical infrastructure.[34][35] It grew to include advanced security controls, graph database models, operational analytics and advanced search capabilities.[36]

In April 2016, the company announced the release of DataStax Enterprise Graph, adding graph data model functionality to DSE.[37]

In March 2017, DataStax announced the release of its DSE platform 5.1, which included improved search capabilities, improved security control, improvements to its Graph data management and improvements to operational analytics performance. DataStax also announced a shift in strategy, with an added focus on customer experience applications. Rather than a new set of technologies, the company started to offer advice on best practice to users of its core DSE platform.[38][36]

In April 2018, DataStax released DSE 6, with the new version focused on businesses using a hybrid cloud computing model, with all the benefits of a distributed cloud database on any public cloud or on-premise, twice the responsiveness and ability to handle twice the throughput.[39][40]

In December 2018, DataStax released DSE 6.7, which offers enterprise customers five key new feature upgrades, including: improved analytics, geospatial search, improved data protection in the cloud, enhanced performance insights and new developer integration tools with Apache Kafka Connector and certified production Docker images.[41]

In April 2020, DataStax released DSE 6.8, offering enterprises new capabilities for bare-metal performance and to support more workloads, and serving as a Kubernetes operator for Cassandra.[42]

DSE 7.0 was introduced in August 2023. It offers enhancements in cloud-native operations and generative AI capabilities, and includes vector search.[43]

Funding and IPO

[edit]

In September 2014, DataStax raised $106 million in a Series E funding round, raising the total investment in the company to $190 million.[3] On June 15, 2022, the company announced it had raised an additional $115 million, at a $1.6 billion valuation.[2][44]

In 2020, Mergermarket reported that DataStax was preparing for an initial public offering that could launch in 2021.[45] However, in June 2022, DataStax CEO Chet Kapoor said that the company would not rush into an IPO.[2]

See also

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

DataStax

View on Grokipedia
from Grokipedia
DataStax, Inc., an company, is an American technology company specializing in distributed database software, particularly solutions built on , designed to manage real-time, large-scale data for enterprise applications including AI and generative AI workloads. Headquartered in , it provides cloud-native, hybrid, and on-premises database platforms that enable scalable data processing for unstructured and multimodal data. Founded in April 2010 by Jonathan Ellis and Matt Pfeil, both former Rackspace engineers who contributed to the early development of , DataStax emerged to commercialize the open-source database for enterprise use. Initially focused on analytics and high-availability systems, the company grew by offering tools for , search, and , serving industries like , healthcare, and . In May 2025, completed its acquisition of DataStax, integrating its technologies into the watsonx AI platform to enhance enterprise AI data management and capabilities. DataStax's core offerings include Astra DB, a serverless, always-on database-as-a-service that supports vector embeddings, time-series data, and graph queries with low-latency performance for AI applications. It also maintains DataStax Enterprise (DSE), an advanced distribution of featuring built-in search, analytics, and security for mission-critical deployments. Complementing these, Langflow is an open-source, low-code platform for developing generative AI workflows, boasting over 100,000 stars. Recognized as a leader in vector databases by Forrester, DataStax's solutions emphasize open-source foundations, multi-cloud flexibility, and integration with AI ecosystems to address data challenges in production-scale environments.

History

Founding and early years

DataStax traces its origins to 2010, when Jonathan Ellis and Matt Pfeil, both former Rackspace engineers who had contributed significantly to the project, co-founded Riptano in . , an open-source distributed database originally developed at to handle large-scale data across commodity servers, had been donated to in 2009, where Ellis served as the initial project chair. Riptano aimed to provide commercial support and services for Cassandra, addressing enterprise needs for and linear scalability in handling massive datasets. Shortly after its , Riptano rebranded to DataStax in late and relocated its headquarters to , to better access Silicon Valley's talent and ecosystem. The company's core mission centered on commercializing for enterprise environments, offering tools, training, and support to enable organizations to deploy distributed databases that could scale horizontally without single points of failure. This focus positioned DataStax as a leader in the emerging space, emphasizing Cassandra's architecture for real-time, high-volume applications like feeds and recommendation engines. In its early years, DataStax gained traction through partnerships and adoption by high-scale users, including , which transitioned to for managing its vast streaming data after experiencing outages with traditional relational databases. Other early adopters in sectors like media and e-commerce leveraged 's fault-tolerant design for applications requiring petabyte-scale storage and low-latency reads. By 2012, DataStax had established itself as the primary commercial steward of , contributing back to the open-source project while building a customer base focused on always-on data infrastructure. DataStax secured its initial funding in October 2010 with a $2.7 million led by , enabling early product development and hiring. This was followed in September 2011 by an $11 million Series B round co-led by Crosslink Capital and , which supported expansion into enterprise sales and further enhancements to Cassandra-based offerings. These investments underscored investor confidence in DataStax's role in bridging open-source innovation with enterprise-grade reliability during the boom of the early 2010s.

Key product developments and expansions

In 2011, DataStax launched DataStax Enterprise (DSE), a commercial extension of that incorporated advanced features such as integrated search via Solr, analytics powered by , and enhanced security mechanisms including LDAP authentication and data auditing. This release marked a significant evolution from the open-source foundation, enabling enterprises to deploy scalable, distributed databases with enterprise-grade operational controls. Throughout the 2010s, DataStax introduced management tools like OpsCenter to improve operational efficiency for Cassandra and DSE clusters. OpsCenter, first released alongside DSE in 2011 as a visual, web-based monitoring and management solution, provided capabilities for cluster visualization, performance monitoring, and automated backups, with subsequent versions adding lifecycle management features in the mid-2010s. These tools addressed key pain points in deploying and maintaining large-scale environments, facilitating broader adoption among organizations requiring and real-time insights. A pivotal shift toward cloud-native services occurred in May 2020 with the general availability of Astra DB, a serverless database-as-a-service (DBaaS) built on , designed for effortless scaling without infrastructure management. This launch simplified deployment in multi-cloud environments, allowing developers to focus on application logic rather than database operations. Later that year, in November 2020, DataStax released K8ssandra, an open-source distribution combining with Kubernetes-native tools like and for storage-optimized, cloud-native deployments. In 2022, DataStax enhanced Astra with capabilities for real-time event streaming and expanded multi-cloud support, including the March introduction of (CDC) to enable streaming of operational data changes and the June general availability of Astra Streaming based on Apache Pulsar for unified event processing across hybrid environments. These developments positioned Astra as a comprehensive platform for handling data in motion, supporting low-latency applications in diverse cloud setups. Building on this momentum, DataStax introduced Astra Block in February 2023, a service integrating data into Astra DB to facilitate and development with real-time, off-chain querying of full datasets. This lowered barriers for integration by providing a centralized, queryable copy of decentralized data, accelerating in . These product advancements drove substantial growth in DataStax's customer base, with adoption by major enterprises including , The Home Depot, Verizon, and collaborative engagements with prior to its 2025 acquisition. By 2024, the company's solutions powered mission-critical workloads for hundreds of organizations, underscoring the scalability and reliability of its Cassandra-based ecosystem.

Acquisition by IBM

On February 25, 2025, IBM announced its intent to acquire DataStax for an undisclosed amount, building on the company's $1.6 billion valuation from its June 2022 funding round. The deal aimed to bolster IBM's capabilities in generative AI by incorporating DataStax's expertise in real-time NoSQL and vector databases, particularly for managing unstructured data in enterprise AI applications. This strategic move addressed key challenges in scaling AI solutions, where handling vast amounts of unstructured data—such as text, images, and videos—remains a bottleneck for many organizations. The acquisition was completed on May 28, 2025, following regulatory approvals, with DataStax integrated as "IBM DataStax" within IBM's watsonx AI and data platform. This integration enabled DataStax's technologies, including its Astra DB , to enhance watsonx.data and support hybrid deployments across on-premises, public , and multi- environments. Post-acquisition, products underwent rebranding to align with the IBM ecosystem, providing customers expanded access to IBM's hybrid infrastructure for greater and reliability in AI workloads. Key leadership from DataStax was initially retained to ensure continuity, with then-CEO Chet Kapoor serving as chairman and CEO of until October 2025, when he joined as vice president of cybersecurity services and observability. These initial changes positioned IBM DataStax to leverage Cassandra's open-source foundation alongside 's AI tools, such as watsonx.ai and Langflow, to streamline production AI and data management at enterprise scale.

Products and services

Astra DB

Astra DB is a serverless, always-on database-as-a-service (DBaaS) launched in 2020, built on to provide global scalability without requiring infrastructure management. Post acquisition in May 2025, Astra DB is integrated with watsonx.data for enhanced AI data management. It enables developers to deploy and manage distributed databases across multiple regions with automatic replication and , handling petabyte-scale data for real-time applications. Core features of Astra DB include multi-cloud deployment on (AWS), (GCP), and , allowing users to select regions within the same provider for multi-region setups. The service offers automatic scaling based on workload demands, eliminating manual provisioning of compute resources. Built-in security encompasses at rest using customer-managed keys and (RBAC) for fine-grained permissions on databases and organizations. Additionally, it supports vector search capabilities optimized for AI workloads, enabling efficient similarity searches on embeddings for applications like retrieval-augmented generation (RAG). Astra DB integrates with the Stargate API to provide REST and GraphQL access to Cassandra data, simplifying CRUD operations without direct CQL usage, though legacy Stargate APIs are being phased out in favor of the Data API. It also supports real-time data ingestion through Astra Streaming, powered by Apache Pulsar, which enables event stream processing and change data capture (CDC) for synchronizing database updates across systems. Astra DB powers high-availability applications in sectors such as for personalized recommendations and , gaming for leaderboards and player data, and IoT for handling sensor streams at scale. For instance, companies like leverage —the core technology underlying Astra DB—for content recommendation systems that serve millions of users with low-latency queries. The pricing model for Astra DB is pay-as-you-go, charged based on consumption of storage, compute (measured in processing capacity units or PCUs), and data transfer, with a free tier available for initial exploration.

DataStax Enterprise

DataStax Enterprise (DSE) was introduced in 2013 as a commercial, unified platform built on , integrating it with for advanced search capabilities, for batch analytics, and later enhancements including for real-time and streaming analytics, as well as graph processing for handling complex relationships in data. Following 's acquisition in May 2025, DSE is supported under IBM until at least December 31, 2027, with new sales conducted through IBM-equivalent offerings. This architecture enabled enterprises to manage mission-critical workloads across operational, analytical, and search use cases within a single system, providing linear scalability and without single points of failure. Key components of DSE include OpsCenter, a visual management tool for monitoring cluster health, performance metrics, automatic backups, , and lifecycle management such as patching and upgrades. DSE Graph, tightly integrated with and leveraging the TinkerPop/ standard, supports real-time traversals and analysis of interconnected datasets, optimized for handling billions of vertices and edges in applications like recommendation engines and network analysis. Additionally, DSE Search provides , fuzzy matching, and geospatial querying powered by Solr, allowing seamless indexing and retrieval of large-scale data volumes. These elements collectively support mixed workloads, from key-value storage to advanced analytics, in a multi-model environment. DSE supports flexible deployment options, including on-premises installations, virtual machines, and hybrid configurations that span multiple data centers or for enhanced and resilience. Hybrid setups enable bursting, where workloads can dynamically scale to resources during peak demands while maintaining on-premises, reducing latency and costs for global operations. features encompass advanced mechanisms like Kerberos and LDAP, auditing, encryption at rest and in transit, and role-based access controls to ensure fine-grained permissions. These capabilities support compliance with standards such as GDPR for privacy and HIPAA for , making DSE suitable for regulated environments. In , DSE powers low-latency, high-volume and detection, as demonstrated by ACI Worldwide's use of DSE to analyze transaction in real-time, enhancing prevention while processing millions of payments securely. In healthcare, it facilitates compliant handling of sensitive for personalized services. These applications highlight DSE's role in enabling resilient, scalable solutions for industries requiring sub-millisecond response times and robust .

AI and generative AI integrations

DataStax's Astra DB incorporates functionality, enabling and Retrieval-Augmented Generation (RAG) for large language models (LLMs) by storing and querying high-dimensional vector embeddings derived from . This supports low-latency retrieval of relevant , improving the accuracy and of generative AI outputs in applications like recommendation systems and knowledge retrieval. Integrations with tools such as AI and further streamline generation and RAG workflows directly within Astra DB. In October 2024, DataStax launched the DataStax AI Platform, developed in collaboration with AI Enterprise, to facilitate the creation of AI-ready databases and the rapid deployment of customized generative AI applications. The platform includes tools for processing, reducing AI development time by up to 60% and accelerating workloads by 19 times compared to traditional methods, while integrating seamlessly with Astra DB for vector search and LLM orchestration. Following 's acquisition of DataStax in May 2025, its technologies were incorporated into the IBM watsonx platform to enhance hybrid cloud AI capabilities, particularly for managing at scale. This integration added Langflow, an open-source tool for low-code workflow orchestration in AI agents and RAG pipelines, and the Hyper-Converged Database (HCD) for automated data harmonization across diverse sources. These enhancements enable watsonx users to build production-grade generative AI applications with improved and in hybrid environments. Key features include real-time streaming via Astra Streaming, built on Apache Pulsar, which handles billions of events for dynamic AI pipelines, and robust support for processing through integrations like Unstructured.io. This allows seamless ingestion, chunking, and embedding of documents, images, and other formats to fuel generative AI models without extensive preprocessing. These AI integrations power enterprise generative AI use cases, such as intelligent chatbots for and for operational insights, as seen in IBM client deployments post-acquisition that leverage watsonx to unlock value from legacy and sources. For example, financial services firms have used these tools to enhance detection via RAG-enhanced LLMs, while retail clients apply them for personalized recommendation engines.

Funding and financial history

Investment rounds

DataStax secured its initial venture funding through a in October 2010, raising $2.7 million from and . This was followed by a Series B round in September 2011, where the company raised $11 million led by Crosslink Capital, with participation from existing investors. The company continued its funding trajectory with a $25 million Series C round in October 2012, led by Meritech Capital Partners and joined by Crosslink Capital and . In July 2013, DataStax closed a $45 million Series D round led by Scale Venture Partners, with contributions from DFJ Growth, Next World Capital, and prior backers including and Crosslink Capital. DataStax's largest early-stage raise came in September 2014 with a $106 million Series E round led by , featuring participation from Clearbridge Investments, Cross Creek Advisors, Wasatch Advisors, Ventures, and Premji Invest, bringing total funding at that point to approximately $190 million. After a period without major equity raises, DataStax returned to the market in May 2021 with a $37.57 million Series F round led by Growth. The company's final pre-2023 funding occurred in June 2022, when it raised $115 million in a growth equity round led by Asset Management, with involvement from RCM Private Markets, EDBI, OnePrime Capital, Hercules Capital, and others; strategic investors across rounds also included Meritech Capital and . Overall, DataStax raised approximately $342.6 million across 10 funding rounds through June 2022, enabling scaling of its enterprise database offerings.
RoundDateAmountLead Investor(s)Other Notable Investors
Series AOctober 2010$2.7M
Series BSeptember 2011$11MCrosslink Capital
Series COctober 2012$25MMeritech Capital PartnersCrosslink Capital,
Series DJuly 2013$45MScale Venture PartnersDFJ Growth, Next World Capital, , Crosslink Capital
Series ESeptember 2014$106MClearbridge Investments, Cross Creek Advisors, Wasatch Advisors, Ventures, Premji Invest
Series FMay 2021$37.57M Growth-
Growth EquityJune 2022$115M Asset ManagementRCM Private Markets, EDBI, OnePrime Capital, Capital

Valuation milestones

DataStax's valuation trajectory began modestly in its early years, reflecting the nascent stage of the database market. Following its Series B funding round of $11 million in September 2011, the company was valued at approximately $50 million, underscoring investor confidence in its Apache Cassandra-based enterprise solutions. By , after raising $106 million in a Series E round led by Caufield & Byers, DataStax's had surged to over $830 million, driven by expanding adoption among enterprises and the growing demand for scalable tools. DataStax achieved status in June 2022, following a $115 million growth equity round led by Asset Management that valued the company at $1.6 billion. This marked an increase from the May 2021 Series F round of $37.6 million, which provided liquidity to employees and early investors, amid a booming and AI data infrastructure sector. Amid market volatility, DataStax explored pre-IPO preparations in 2021 and 2022, with reports indicating potential public offerings as the company scaled its subscription-based . However, cooling tech markets and rising interest rates led to a strategic pivot away from an IPO. By 2024, DataStax's estimated annual recurring (ARR) reached between $200 million and $300 million, propelled by subscription growth in AI-integrated database services. The company's independent financial journey concluded with its acquisition by in May 2025, in a deal valued at or above its $1.6 billion peak, integrating DataStax's capabilities into IBM's watsonx AI ecosystem.

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  64. https://www.datacenterknowledge.com/investing/enterprise-cassandra-player-datastax-raises-106m
  65. https://news.crunchbase.com/cloud/datastax-valuation-unicorn-vc-goldman/
  66. https://www.businessinsider.com/cloud-startups-raised-vc-funding-this-year-andreessen-horowitz-lightspeed-2022-7
  67. https://www.forbes.com/sites/petercohan/2018/07/29/datastax-getting-ready-for-ipo-targeting-46b-database-market/
  68. https://getlatka.com/companies/datastax
  69. https://aragonresearch.com/ibm-announces-intent-to-acquire-datastax/
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