DBMS > Atos Standard Common Repository vs. Spark SQL vs. SQLite vs. VoltDB vs. YDB

System Properties Comparison Atos Standard Common Repository vs. Spark SQL vs. SQLite vs. VoltDB vs. YDB

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

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

Widely used embeddable, in-process RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Relational DBMS

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

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

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

spark.apache.org/sql

www.sqlite.org

www.voltdb.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

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

www.sqlite.org/docs.html

docs.voltdb.com

ydb.tech/en/docs

Developer

Atos Convergence Creators

Apache Software Foundation

Dwayne Richard Hipp

VoltDB Inc.

Yandex

Initial release

2016

2014

2000

2010

2019

Current release

1703

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

Apache 2.0; commercial license 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

Scala

Java, C++

Server operating systems

Linux

Linux
OS X
Windows

server-less

Linux
OS X

for development

Linux

Data scheme

Schema and schema-less with LDAP views

yes

dynamic column types

yes

Flexible Schema (defined schema, partial schema, 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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

only a subset of SQL 99

SQL-like query language (YQL)

APIs and other access methods

LDAP

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
JDBC
RESTful HTTP/JSON API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages with LDAP bindings

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

Active-passive shard 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

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of specific operations

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

Access rights defined for Yandex Cloud users

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