Kinetica

What Kinetica does

Kinetica Systems, Inc. is a private database software vendor founded in 2016 and headquartered in San Francisco (with additional offices in San Diego), operating a GPU-accelerated, vectorized, lockless distributed database engine that consolidates five specialty analytical workloads — vector search, graph analytics, geospatial, time-series, and key-value lookup — into a single SQL interface. The engine is built natively for modern GPU+CPU hardware (marketed as 'Accelerated by NVIDIA'), processes data simultaneously across cores rather than row-by-row, and is engineered for sub-50ms queries on billion-record datasets with sustained ingest rates of 800k records/sec on 8-node clusters.

Kinetica distributes the platform through three editions — Enterprise (on-premise or private cloud, quote-based subscription), Kinetica Cloud (managed service), and a free Developer Edition (Docker, full feature set, no credit card) — plus add-on modules including Reveal (BI/visualization), SQL-GPT (NL-to-SQL), GAdmin (cluster admin), Kinetica Workbench, KAgent, KiFS, and the 2025-launched Agent Skills open-source toolkit for AI agent backends. The company sells to enterprise and federal buyers in defense and intelligence, financial services, logistics and supply chain, telecom, energy, healthcare, and the AI/data-stack modernization segment, with named customers including Citi, Verizon, USPS, FAA, L2 Data, Cary Health, and Enverus. Distribution combines direct enterprise field sales, self-serve cloud and Docker channels, and an AWS Marketplace listing, supported by a documented go-to-market spanning content, technical documentation, GitHub, events, and partner co-marketing.

The company has raised approximately $77.4M in disclosed venture funding (notably a $50M Series B in 2017 led by Canvas Prime and Meritech Capital Partners, with Citi Ventures and GreatPoint Ventures participating) and more recently has deployed balance-sheet capital into AI-adjacent startups, including a participation in Limitless Labs' $20M Series A in June 2026.

Name

Kinetica

Legal name

Kinetica Systems, Inc.

Website

https://kinetica.com

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

51–100 employees

Short description

Kinetica is a private database vendor offering a GPU-accelerated, vectorized distributed database that consolidates vector, graph, geospatial, time-series, and key-value analytics into a single SQL engine. It sells Enterprise, Cloud, and free Developer editions to federal, financial services, telecom, logistics, energy, healthcare, and AI-agent customers.

Ownership category

akta.pro rank

Product category

Real-time analytical database

NAICS

Software Publishers (5132), Software Publishers (513210), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (5182)

SIC

Services-Prepackaged Software (7372), Services-Computer Processing & Data Preparation (7374)

akta.pro primary industry

Data & Analytics Platforms (Data Warehousing, Lakes, Streaming) (HDABAAAF)

akta.pro secondary industries

Query Engines & SQL Analytics Layers for Warehouses/Lakes (HDAEABAI), Data Warehouse/Lakehouse Performance Optimization & Cost Management (HDAEABAL), Real-Time Decisioning & Next-Best-Action Engines (HDAAAHAK)

Keywords

• Real-time analytics database
• GPU-accelerated database
• Vector search engine
• Time-series database
• Geospatial analytics

Headquarters

HQ city

Vienna

HQ country

United States

HQ region

North America

Offices2 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Infrastructure, Marketing or Sales, Operations

Revenue model

1. Enterprise Edition License: On-premise or cloud-deployed enterprise database licensing with full feature access for large organizations
2. Kinetica Cloud: Cloud-hosted subscription service providing managed database capabilities
3. Developer Edition: Free tier with full feature set for individual developers and evaluation purposes, designed to drive adoption and conversion to paid enterprise tiers
4. Professional Services: Implementation, training, and support services for enterprise deployments

Pricing tiers

Go-to-market motion2 records

Distribution channels4 records

Marketing channels9 records

Core offering

Kinetica sells a GPU-accelerated, vectorized, distributed database engine that performs real-time analytical workloads — vector search, graph, geospatial, time-series, and key-value lookups — within a single SQL interface. It is offered as an Enterprise Edition (on-premise/private cloud), a fully managed Cloud service, and a free Developer Edition (Docker), targeting large organizations in defense, finance, logistics, telecom, and energy that need sub-second query performance at scale.

Product overview

Kinetica is a unified GPU-accelerated analytical database that replaces five specialty databases (vector, graph, spatial, time-series, key-value) with a single vectorized engine. The core product is the Kinetica Database Engine, available as Kinetica Cloud (managed service), Kinetica Enterprise Edition (on-premises), and Kinetica Developer Edition (free, full-feature local deployment). The product portfolio includes Agent Skills (open-source AI agent toolkit on GitHub), Reveal (built-in BI visualization), SQL-GPT (natural language to SQL), GAdmin (administration GUI), Kinetica Workbench (SQL workbook UI), KAgent (cluster monitoring/management agent), and KiFS (native file system). All capabilities are accessed through a single SQL interface with SDKs in Python, Java, JavaScript, C++, and Node.js, plus REST API, JDBC/ODBC, PostgreSQL proxy, and MCP server.

Differentiator

Problem solved

Functional benefit

Brands

• Kinetica Cloud: Cloud deployment option for Kinetica database
• Kinetica Developer Edition
• Kinetica Enterprise Edition
• Reveal
• GAdmin
• KAgent
• KiSQL

Products and services

• Kinetica Database Engine GPU-accelerated, vectorized, distributed database engine that natively handles vector search, graph analytics, geospatial analytics, time-series, and key-value workloads within a single SQL interface. Designed for enterprise and developer users running real-time, multi-modal analytics at scale.
• Kinetica Cloud Fully managed cloud deployment of the Kinetica database engine with monthly subscription billing, designed for mid-market and enterprise teams that want sub-second multi-modal analytics without operating the underlying GPU infrastructure.
• Kinetica Enterprise Edition On-premises or private cloud deployment of the Kinetica engine with full feature access, high availability, advanced security controls, and enterprise support. Targeted at large organizations in defense, finance, federal, telecom, energy, and logistics that need to run the platform inside their own environment.
• Kinetica Developer Edition Free, full-feature local deployment of the Kinetica engine distributed via Docker (docker run -p 9191:9191 kinetica/developer-edition) with no time limit and no credit card required. Targets individual developers, data engineers, and small teams evaluating the platform before adopting Enterprise or Cloud.

Quantifiable outcome

• 240x faster spatial queries than PostGIS
• +8 more outcomes

Named customers7 records

Segments6 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration10 records

AI capability7 records

Feature9 records

Partnerships

One partnership is on record.

• NVIDIAcoreTechnology or IntegrationNVIDIA partnership for GPU acceleration. Kinetica is 'Accelerated by NVIDIA' and built natively on NVIDIA GPU infrastructure. The platform leverages NVIDIA T4 GPUs and CUDA for high-performance vectorized processing.

Scale indicators8 records

Recent moves6 records

Expansion highlights5 records

Direct peers

• ClickHouse: ClickHouse is a column-oriented open-source OLAP database that competes head-to-head with Kinetica for real-time analytical workloads on large datasets. Both target sub-second queries at billion-row scale and overlap directly on Kinetica's key-value and time-series benchmarks (Kinetica claims 10x throughput vs ClickHouse on key-value).
• SingleStore: SingleStore is a distributed real-time database combining transactional and analytical workloads, directly comparable on Kinetica's time-series benchmarks (Kinetica claims 3x faster than SingleStore). Both target enterprises needing real-time ingest and analytics with SQL.
• StarRocks: StarRocks is a high-performance MPP analytical database competing for the same sub-second analytical queries on large datasets. It is the closest open-source competitor to Kinetica's unified OLAP profile across vector, time-series, and geospatial use cases.
• Aerospike: Aerospike is a real-time NoSQL data platform built for sub-millisecond processing at scale. It competes with Kinetica for real-time ingest-plus-query workloads in financial services, ad tech, and defense — the same verticals Kinetica targets.

Emerging players

• DuckDB / MotherDuck: DuckDB (and its cloud sibling MotherDuck) is an in-process analytical database optimized for fast OLAP queries. While primarily CPU-native, it competes for many of the same developer-led analytical workloads that Kinetica targets with its Developer Edition and could erode the developer-led acquisition funnel.
• Milvus: Milvus is a leading open-source vector database used for AI/ML similarity search. Kinetica explicitly benchmarks 10x faster than Milvus on vector indexing; the two compete for the same AI/RAG workloads where vector search is the primary requirement.
• Neo4j: Neo4j is the leading native graph database, competing for graph analytics workloads in fraud detection, knowledge graphs, and network analysis. Kinetica claims 6x faster graph queries than Neo4j at scale and pitches itself as a graph alternative within a unified SQL engine.
• TimescaleDB: TimescaleDB is a Postgres-native time-series database serving many of the same industrial IoT and operational telemetry use cases that Kinetica's Logistics and Energy customers target. It provides a CPU-only, Postgres-compatible alternative for time-series workloads within Kinetica's portfolio.

Broad incumbents

• Snowflake: Snowflake is the dominant cloud data warehouse with broad analytical capabilities and a hyperscaler-scale GTM motion. While not GPU-native, it competes head-on for enterprise analytical budgets and could compress Kinetica's deal sizes if Snowflake adds vector or real-time GPU features.
• Databricks: Databricks provides a unified lakehouse platform spanning SQL analytics, ML, and AI workloads. It overlaps with Kinetica's positioning as a single engine for multi-modal analytics and is a likely consolidation competitor for AI agent infrastructure budgets.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/kineticadb
• LinkedInlinkedin.com/company/kinetica

Revenue estimate

Valuation estimate

Number of profiles

Profiles6 records

Funding overview

Funding rounds4 records

Investors4 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments1 record

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Kinetica