DBMS > Atos Standard Common Repository vs. Drizzle vs. Geode vs. Microsoft SQL Server vs. SwayDB

System Properties Comparison Atos Standard Common Repository vs. Drizzle vs. Geode vs. Microsoft SQL Server vs. SwayDB

Editorial information provided by DB-Engines

Name

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

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Microsofts flagship relational DBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

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

geode.apache.org

www.microsoft.com/en-us/sql-server

swaydb.simer.au

Technical documentation

geode.apache.org/docs

learn.microsoft.com/en-US/sql/sql-server

Developer

Atos Convergence Creators

Drizzle project, originally started by Brian Aker

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Simer Plaha

Initial release

2016

2008

2002

1989

2018

Current release

1703

7.2.4, September 2012

1.1, February 2017

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

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++

Java

C++

Scala

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

Linux
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

yes

with proprietary extensions

SQL-like query language (OQL)

yes

APIs and other access methods

LDAP

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

All languages with LDAP bindings

C
C++
Java
PHP

.Net
All JVM based languages
C++
Groovy
Java
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

yes, but depending on the SQL-Server Edition

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

Eventual Consistency

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

yes, on a single node

ACID

Atomic execution of operations

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights per client and object definable

fine grained access rights according to SQL-standard

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