Dremio vs Matano
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts. | 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. |
Democratize all your data;
Make your data engineers more productive;
Accelerate your favorite tools;
Self service, for everybody
| 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 |
Statistics | |
GitHub Stars - | GitHub Stars 1.6K |
GitHub Forks - | GitHub Forks 116 |
Stacks 116 | Stacks 0 |
Followers 348 | Followers 2 |
Votes 8 | Votes 0 |
Pros & Cons | |
Pros
Cons
| No community feedback yet |
Integrations | |
What are some alternatives to Dremio, Matano?
Papertrail
Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.
Logmatic
Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.
Loggly
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.
Google BigQuery
Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Amazon Redshift
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Logentries
Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.
Logstash
Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
Let's Encrypt
It is a free, automated, and open certificate authority brought to you by the non-profit Internet Security Research Group (ISRG).
Graylog
Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.
