Overview
Cockroach Labs is the creator of CockroachDB, the cloud-native, resilient, distributed SQL database enterprises worldwide trust to run mission-critical AI and other applications that scale fast, avert and survive disaster, and thrive everywhere. It runs on the Big 3 clouds, on prem, and in hybrid configurations powering Fortune 500, Forbes Global 2000, and Inc. 5000 brands, and game-changing innovators, including OpenAI, CoreWeave, Adobe, NETFLIX, Booking.com, DoorDash, FANDUEL, Cisco Systems, P&G, UiPath, FORTINET, Roblox, EA, BestBuy, SpaceX, NVIDIA, The VA, Squarespace, The Home Depot, and Hewlett Packard Enterprise. Cockroach Labs has customers in 40+ countries across all world regions, 25+ verticals, and 50+ Use Cases. Cockroach Labs operates its own ISV Partner Ecosystem powering Payments, Identity Management (IDM/IAM), Banking & Wallet, Trading, and other high-demand use cases. Cockroach Labs is an AWS Partner of the Year finalist and has achieved AWS Competency Partner certifications in Data & Analytics and Financial Services (FSI). CockroachDB pricing is available at https://www.cockroachlabs.com/pricing/
Vector, RAG, and GenAI Workloads
CockroachDB includes native support for the VECTOR data type and pgvector API compatibility, enabling storage and retrieval of high-dimensional embeddings. These vector capabilities are critical for Retrieval-Augmented Generation (RAG) pipelines and GenAI workloads that rely on similarity search and contextual embeddings. By supporting distributed vector indexing within the database itself, CockroachDB removes the need for external vector stores and allows AI applications to operate against a single, consistent data layer.
C-SPANN Distributed Indexing
At the core of CockroachDB’s vector search capabilities is the C-SPANN indexing engine. C-SPANN provides scalable approximate nearest neighbor (ANN) search across billions of vectors while supporting incremental updates, real-time writes, and partitioned indexing. This ensures low-latency retrieval in the tens of milliseconds, even under high query throughput. The algorithm eliminates central coordinators, avoids large in-memory structures, and leverages CockroachDB’s sharding and replication to deliver scale, resilience, and global consistency.
Machine Learning and Apache Spark Integration
CockroachDB integrates with modern ML workflows by supporting embeddings generated through frameworks such as AWS Bedrock and Google Vertex AI. Its compatibility with the PostgreSQL JDBC driver allows seamless integration with Apache Spark, enabling distributed processing and advanced analytics on CockroachDB data.
PostgreSQL Compatibility and JSON Support
CockroachDB speaks the PostgreSQL wire protocol, so applications, drivers, and tools designed to work with Postgres can connect to CockroachDB without modification, enabling seamless use of familiar SQL features and integration with the wider Postgres ecosystem. This includes support for advanced data types such as JSON and JSONB, which allow developers to store and query semi-structured data natively.
Geospatial and Graph Capabilities
CockroachDB also provides first-class geospatial data support, allowing developers to store, query, and analyze spatial data directly in SQL. For graph workloads, CockroachDB employs JSON flexibility to represent relationships and delivers query capabilities for graph-like traversals. This combination enables hybrid applications that merge relational, geospatial, document, and graph data within a single platform.
Analytics, BI, and Integration
To support high-performance analytics and BI, CockroachDB supports core analytical use cases and functions including Enterprise Data Warehouse, Lakehouse, and Event Analytics, and offers materialized views for precomputing complex joins and aggregations. Its PostgreSQL wire compatibility ensures direct connectivity with all relevant BI and analytics apps and tools including Amazon Redshift, Snowflake, Kafka, Google BigQuery, Salesforce Tableau, Databricks, Cognos, Looker, Grafana, Power BI, Qlik Sense, SAP, SAS, Sisense, and TIBCO Spotfire. Data scientists can interact with CockroachDB through Jupyter Notebooks, querying structured and semi-structured data and loading results for analysis. Change data capture (CDC) streams provide real-time updates to analytics pipelines and feature stores, keeping downstream systems fresh and reliable. Columnar vectorized execution accelerates query processing, optimizes transactional throughput, and minimizes latency for demanding distributed workloads.
MOLT AI-Powered Migration
Organizations often know their data infrastructure is not supporting the business, but find it too painful to change. CockroachDB’s MOLT (Migrate Off Legacy Technology) is designed to enable safe, minimal-downtime database migrations from legacy systems to CockroachDB. MOLT Fetch supports data migration from PostgreSQL, MySQL, SQL Server, and Oracle, with SQL Server and DB2 coming soon. CockroachDB also has a portfolio of data replication platform integrations including Precisely, Striim, Qlik, Confluent, IBM, etc.
Together, these capabilities ensure that CockroachDB supports both operational and analytical workloads, bridging traditional SQL applications with emerging Gen AI and ML use cases.
Average Rating: 4.3/5.0
Total Reviews: 27
How Do G2 Users Rate CockroachDB?
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Ease of Use: 8.9/10 (Category avg: 8.5/10)
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Workload Management: 8.1/10 (Category avg: 8.3/10)
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Data Schema: 8.1/10 (Category avg: 8.6/10)
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Query Language: 8.1/10 (Category avg: 8.6/10)
Who Is the Company Behind CockroachDB?
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Seller: Cockroach Labs
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Year Founded: 2015
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HQ Location: New York, NY
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Twitter: @CockroachDB
13,571 Twitter followers
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LinkedIn® Page: www.linkedin.com
724 employees on LinkedIn®
Who Uses This Product?
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Top Industries: Computer Software, Information Technology and Services
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Company Size: 55% Small, 34% Medium
What Do G2 Reviewers Say About CockroachDB?
AI-generated summary from verified user reviews
Pros
- Users appreciate the ease of management and reliability of CockroachDB, enabling them to focus on development without disruptions.
- Users value the ease of use of CockroachDB, enjoying its straightforward SQL implementation and seamless scalability.
- Users highlight CockroachDB's seamless performance and automatic scalability, ensuring reliable data management without operational headaches.
- Users appreciate the scalability of CockroachDB, enabling seamless management of distributed databases across multiple locations.
- Users value the automatic scaling and reliability of CockroachDB, making big data management effortless and efficient.
Cons
- Users find the learning curve steep for CockroachDB, especially regarding configuration and understanding its unique operational aspects.
- Users find CockroachDB's setup and configuration to have a steep complexity for beginners, impacting overall user experience.
- Users find the difficult learning curve of CockroachDB challenging, especially for beginners trying to optimize configuration.
- Users face feature limitations in CockroachDB due to a steep learning curve and less mature advanced functionalities.
- Users note the complexity and steep learning curve of CockroachDB, which may hinder optimal configuration and understanding.
What Are G2 Users Discussing About CockroachDB?
