What is Matano?
Matano is the open source security lake platform for AWS. It lets you ingest petabytes of security and log data from various sources, store and query them in a data lake, and create Python detections as code for realtime alerting.
Matano is a tool in the Big Data Tools category of a tech stack.
Matano is an open source tool with 1.5K GitHub stars and 109 GitHub forks. Here’s a link to Matano's open source repository on GitHub
Matano Integrations
Python, Amazon S3, Kafka, Apache Spark, and Amazon Athena are some of the popular tools that integrate with Matano. Here's a list of all 5 tools that integrate with Matano.
Matano's Features
- Collect data from all your sources
- Ingest, transform, normalize log data
- Store data in S3 object storage
- Apache Iceberg Data lake
- Serverless
- Detections as code
Matano Alternatives & Comparisons
What are some alternatives to Matano?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system
that supports an extended subset of the SQL standard, including
transactions, foreign keys, subqueries, triggers, user-defined types
and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
Related Comparisons
No related comparisons found