DataStax Enterprise

Accelerates AI application development.

Uses Langflow, an AI development platform.

Integrates with Astra DB, a near-zero latency database.

Built-in support for vector search.

Built-in support for knowledge graph functionality.

Tools designed to make AI development easier.

Provides capabilities for building AI agents.

Offers comprehensive tools for managing data.

Combines NoSQL database features with vector database capabilities.

Streamlines the deployment process for AI applications.

Provides a unified platform for AI development.

Allows easy integration of data into applications.

Functions as an AI Platform as a Service.

Supports orchestration of AI workflows.

Serves as a foundational data platform.

Offers a suite of integrated services.

Facilitates deployment of AI applications at scale.

Supports deployment in cloud environments.

Supports self-managed (on-premise) deployments.

Works with major cloud providers.

Aims to ensure consistent high performance.

Helps reduce total cost of ownership.

Focuses on security and scalability for production environments.

Simplifies creating and understanding complex logic flows, particularly for RAG.

Offers ready-to-use integrations for faster testing with real data.

Provides a low-code integrated development environment.

Accelerates the testing and iteration cycles.

Compatible with open-source tools and integrations.

Airbyte, Amazon Bedrock, Anthropic, Azure, Bing, Cassandra, Chroma, Clickhouse, Cohere, Composio, Confluence, Couchbase, CrewAI, DuckDuckGo, Evernote, Firecrawl, GitHub, Glean, Gmail, Google Cloud, Google Drive, Groq, Hugging Face, LangChain, MeriTalk, Meta, Milvus, Mistral, MongoDB, Notion, NVIDIA, Ollama, OpenAI.

Helps manage data effectively for relevant AI applications.

Enhances the relevance of search queries.

Aims to minimize AI model hallucinations.

Enables efficient handling and search of vector embeddings.

Supports management of knowledge graph data.

Provides extremely low-latency data access.

Built on the highly scalable and available Apache Cassandra database.

Supports hybrid cloud deployment models.

Offers specialized expertise for Apache Cassandra.

Based on Apache Cassandra, providing its core benefits.

Adds features for reliable operations.

Includes tools for monitoring database performance and health.

Provides enterprise-grade security features.

Supports analytical workloads.

Integrated search functionalities.

Tools for generating reports from data.

Designed for efficient data replication and distribution.

Supports various data models including JSON/document, key-value, tabular, and graphs.

For storing very large datasets (replaces CFS).

Includes new fuzzy search, advanced configuration of search indexing, improved data loading, geospatial querying, Kerberos support, and customizable visualizations for graph data.

Allows permissions on table rows and search indexes.

Manages web services via DSE Proxy.

Integrates with DSE Unified Authentication (LDAP or internal).

Improved search performance using Apache Solr.

Streamlines operations and development for search indexes.

Re-designed using Change Data Capture (CDC) logs for configurable replication, suitable for sporadic connectivity.

Visually navigates database objects, creates and tunes CQL queries, with intelligent CQL editor, syntax highlighting, validation, code completion, and query profiling.

More complete profiling for graph queries in DSE Studio.

Colors and sizes vertices by label/property value, custom shapes and icons.

Improved schema display.

MemoryOnlyStrategy works with compression.

Operational performance improvements.

Better command-line assistance.

Enhances command-line productivity.

Better management tools.

Automatically graphs stress test results.

Allows using clustering columns in WHERE clauses without secondary index if ALLOW FILTERING is used.

Recreates dropped tables and replays commitlog for data recovery.

Improved support for Just a Bunch Of Disks compaction and backup.