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What is pganalyze?

pganalyze is a Postgres performance optimization product for engineering teams. It captures query performance, wait events, and other critical data, finds the root cause of slow queries, bad indexes, and table bloat in minutes, and lets you investigate safely with AI tools such as Claude Code through the pganalyze MCP Server. More than 700 teams, including Notion, Auto Trader UK, and Fivetran, use pganalyze. With pganalyze, teams: ✓ Find and fix slow queries before customers notice ✓ Ship index and plan changes with confidence ✓ Keep autovacuum running smoothly ✓ Spend on tuning, not bigger instances ✓ Make every engineer and AI agent a Postgres expert ✓ Meet security and compliance standards The Index Advisor, Query Advisor, and VACUUM Advisor recommend indexes, query rewrites, and autovacuum settings, and pganalyze Workbooks let you test and validate a fix before you ship. The pganalyze collector filters PII on your own infrastructure before anything leaves, and sign-in supports SAML SSO. pganalyze works with Amazon RDS and Aurora, Google Cloud SQL and AlloyDB, Azure Database for PostgreSQL, Heroku, Crunchy Bridge, Aiven, Supabase, Neon, and self-managed Postgres, including Kubernetes. Use it as a cloud service, or self-host with pganalyze Enterprise Server.

What is PostgresML?

PostgresML is an all-encompassing platform embedded within a PostgreSQL extension, enabling users to create models that are not only more efficient and rapid but also scalable within their database setting. Users have the opportunity to explore the SDK and experiment with open-source models that are hosted within the database. This platform streamlines the entire workflow, from generating embeddings to indexing and querying, making it easier to build effective knowledge-based chatbots. Leveraging a variety of natural language processing and machine learning methods, such as vector search and custom embeddings, users can significantly improve their search functionalities. Moreover, it equips businesses to analyze their historical data via time series forecasting, revealing essential insights that can drive strategy. Users can effectively develop statistical and predictive models while taking advantage of SQL and various regression techniques. The integration of machine learning within the database environment facilitates faster result retrieval alongside enhanced fraud detection capabilities. By simplifying the challenges associated with data management throughout the machine learning and AI lifecycle, PostgresML allows users to run machine learning and large language models directly on a PostgreSQL database, establishing itself as a powerful asset for data-informed decision-making. This innovative methodology ultimately optimizes processes and encourages a more effective deployment of data resources. In this way, PostgresML not only enhances efficiency but also empowers organizations to fully capitalize on their data assets.

Media

Media

Integrations Supported

PostgreSQL
Honeycomb
Okta

Integrations Supported

PostgreSQL
Apache Superset
BERT
C++
Elixir
Falcon
Jupyter Notebook
Llama 2
Llama 3.1
Llama 3.2
Microsoft Power BI
Mixtral 8x22B
Mixtral 8x7B
Node.js
Pixtral Large
Ruby
Scala
Visual Studio Code

API Availability

Has API

API Availability

Has API

Pricing Information

$149 per month
Free Trial Offered?

Pricing Information

$.60 per hour
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

pganalyze

Date Founded

2012

Company Location

United States

Company Website

pganalyze.com

Company Facts

Organization Name

PostgresML

Company Website

postgresml.org

Categories and Features

Database Monitoring

Not specified

Log Monitoring

Not specified

Categories and Features

AI Development

Not specified

AI Tools

Not specified

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