Apache Parquet vs Stroom
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language. | It is a data processing, storage and analysis platform. It is scalable - just add more CPUs / servers for greater throughput. It is suitable for processing high volume data such as system logs, to provide valuable insights into IT performance and usage. |
Columnar storage format;Type-specific encoding;
Pig integration;
Cascading integration;
Crunch integration;
Apache Arrow integration;
Apache Scrooge integration;Adaptive dictionary encoding;
Predicate pushdown;
Column stats | Receive and store large volumes of data such as native format logs. Ingested data is always available in its raw form; Create sequences of XSL and text operations, in order to normalise or export data in any format. It is possible to enrich data using lookups and reference data; Easily add new data formats and debug the transformations if they don't work as expected; Create multiple indexes with different retention periods. These can be sharded across your cluster; Run queries against your indexes or statistics and view the results within custom visualisations; Record counts or values of items over time |
Statistics | |
GitHub Stars - | GitHub Stars 452 |
GitHub Forks - | GitHub Forks 62 |
Stacks 97 | Stacks 1 |
Followers 190 | Followers 3 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Apache Parquet, Stroom?
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.
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.
Microsoft SQL Server
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
SQLite
SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Memcached
Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
MariaDB
Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
RethinkDB
RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
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.
