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What is ZeusDB?

ZeusDB is an advanced data platform designed to address the intricate demands of modern analytics, machine learning, real-time data insights, and hybrid data management solutions. This state-of-the-art system effectively merges vector, structured, and time-series data within one cohesive engine, enabling functionalities such as recommendation engines, semantic search capabilities, retrieval-augmented generation, live dashboards, and the deployment of machine learning models from a single source. Featuring ultra-low latency querying and real-time analytics, ZeusDB eliminates the need for multiple databases or caching solutions, streamlining operations. Moreover, it offers developers and data engineers the opportunity to extend its capabilities using Rust or Python, with flexible deployment options in on-premises, hybrid, or cloud setups while maintaining compliance with GitOps/CI-CD practices and integrating built-in observability. Its powerful characteristics, including native vector indexing methods like HNSW, metadata filtering, and sophisticated query semantics, enhance similarity searching, hybrid retrieval strategies, and rapid application development cycles. As a result, ZeusDB is set to transform how organizations manage data and conduct analytics, making it an essential asset in today’s data-driven environment. By harnessing its innovative features, businesses can achieve greater efficiency and effectiveness in their data operations.

What is Tiger Data?

Tiger Data is a next-generation PostgreSQL++ platform engineered for developers, devices, and AI agents that need scalable, intelligent data systems. As the company behind TimescaleDB, it extends PostgreSQL into a universal foundation for time-series analytics, real-time observability, AI retrieval, and agentic applications. The platform’s modular design introduces key primitives — Interface, Forks, Memory, Search, Materialization, and Scale — which collectively empower developers to build, deploy, and automate data-intensive workloads with ease. With Forks, users can instantly clone environments for testing or development, while Memory ensures contextual persistence across agents and time. Its hybrid search engine merges BM25 ranking with vector retrieval, enabling semantic and structured queries within a single system. Built-in time-series and streaming support allows sub-second analytics on billions of rows, while continuous aggregates and columnar compression optimize performance and cost. Tiger Cloud offers a fully managed deployment with multi-AZ resilience, encryption, SSO, and tiered storage for maximum efficiency. From IoT telemetry and financial data to AI observability and agent context storage, Tiger Data unifies real-time and analytical workloads under one Postgres-compatible umbrella. Companies like Cloudflare, Toyota, Polymarket, and Hugging Face rely on Tiger to simplify their infrastructure while scaling insights globally. With over 20,000 developers and a 4.7 G2 score, Tiger Data defines the future of PostgreSQL — smarter, faster, and built for the next era of intelligent systems.

Media

Media

Integrations Supported

LangChain
Python
Rust

Integrations Supported

LangChain
Amazon S3
Apache Kafka
Datadog
Grafana Cloud
Hugging Face
Llama
OpenAI
Polymarket
PostgreSQL
Prometheus
SQL
Snowflake
Tableau
TimescaleDB

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

$30 per month
Free Trial Offered?

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ZeusDB

Date Founded

2012

Company Location

United States

Company Website

www.zeusdb.com

Company Facts

Organization Name

Tiger Data

Date Founded

2015

Company Location

United States

Company Website

www.tigerdata.com

Categories and Features

Relational Database

Not specified

Vector Databases

Not specified

Categories and Features

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