DBMS > Atos Standard Common Repository vs. PostGIS vs. SWC-DB vs. Tarantool vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. PostGIS vs. SWC-DB vs. Tarantool vs. Valentina Server

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

Spatial extension of PostgreSQL

A high performance, scalable Wide Column DBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Object-relational database and reports server

Primary database model

Document store
Key-value store

Spatial DBMS

Wide column store

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

Time Series DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	23.90
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

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

postgis.net

github.com/kashirin-alex/swc-db
www.swcdb.org

www.tarantool.io

www.valentina-db.net

Technical documentation

postgis.net/documentation

www.tarantool.io/en/doc

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Atos Convergence Creators

Alex Kashirin

Paradigma Software

Initial release

2016

2005

2020

2008

1999

Current release

1703

3.4.2, February 2024

0.5, April 2021

2.10.0, May 2022

5.7.5

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

Open Source

GPL V3

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

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++

C and C++

Server operating systems

Linux

BSD
Linux
macOS

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

Typing

predefined data types such as float or date

optional

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

yes

SQL-like query language

Full-featured ANSI SQL support

yes

APIs and other access methods

LDAP

Proprietary protocol
Thrift

Open binary protocol

ODBC

Supported programming languages

All languages with LDAP bindings

C++

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

yes

Triggers

yes

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

based on PostgreSQL

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

LDAP bind authentication

yes

based on PostgreSQL

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard

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More resources

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