DBMS > Atos Standard Common Repository vs. Postgres-XL vs. Prometheus vs. ReductStore vs. Vitess

System Properties Comparison Atos Standard Common Repository vs. Postgres-XL vs. Prometheus vs. ReductStore vs. Vitess

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-source Time Series DBMS and monitoring system

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

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

www.postgres-xl.org

prometheus.io

github.com/reductstore
www.reduct.store

vitess.io

Technical documentation

www.postgres-xl.org/documentation

prometheus.io/docs

www.reduct.store/docs

vitess.io/docs

Developer

Atos Convergence Creators

ReductStore LLC

The Linux Foundation, PlanetScale

Initial release

2016

2014

since 2012, originally named StormDB

2015

2023

2013

Current release

1703

10 R1, October 2018

1.9, March 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

Open Source

Business Source License 1.1

Open Source

Apache Version 2.0, commercial licenses 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.

Implementation language

Java

C++, Rust

Server operating systems

Linux

Linux
macOS

Linux
Windows

Docker
Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

Numeric data only

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

XML type, but no XML query functionality

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

with proprietary extensions

APIs and other access methods

LDAP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Multi-source replication
Source-replica replication

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

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

MVCC

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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