DBMS > Atos Standard Common Repository vs. ClickHouse vs. RocksDB vs. Spark SQL vs. TerarkDB

System Properties Comparison Atos Standard Common Repository vs. ClickHouse vs. RocksDB vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Spark SQL is a component on top of 'Spark Core' for structured data processing

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Key-value store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

clickhouse.com

rocksdb.org

spark.apache.org/sql

github.com/bytedance/terarkdb

Technical documentation

clickhouse.com/docs

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Atos Convergence Creators

Clickhouse Inc.

Facebook, Inc.

Apache Software Foundation

ByteDance, originally Terark

Initial release

2016

2013

2014

2016

Current release

1703

v24.4.1.2088-stable, May 2024

8.11.4, April 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache 2.0

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C++

Scala

C++

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

APIs and other access methods

LDAP

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

C++ API
Java API

JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages with LDAP bindings

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

key based and custom

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

LDAP bind authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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