DBMS > Atos Standard Common Repository vs. openGauss vs. Spark SQL vs. SQLite vs. SurrealDB

System Properties Comparison Atos Standard Common Repository vs. openGauss vs. Spark SQL vs. SQLite vs. SurrealDB

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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Widely used embeddable, in-process RDBMS

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

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

gitee.com/opengauss
opengauss.org

spark.apache.org/sql

www.sqlite.org

surrealdb.com

Technical documentation

docs.opengauss.org/en
gitee.com/opengauss/docs

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

www.sqlite.org/docs.html

surrealdb.com/docs

Developer

Atos Convergence Creators

Huawei and openGauss community

Apache Software Foundation

Dwayne Richard Hipp

SurrealDB Ltd

Initial release

2016

2019

2014

2000

2022

Current release

1703

3.0, March 2022

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

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++, Java

Scala

Rust

Server operating systems

Linux

Linux
OS X
Windows

server-less

Linux
macOS
Windows

Data scheme

Schema and schema-less with LDAP views

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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

ANSI SQL 2011

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

LDAP

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

All languages with LDAP bindings

C
C++
Java

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning (by range, list and hash)

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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, groups and roles according to SQL-standard

yes, based on authentication and database rules

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