DBMS > atoti vs. Datomic vs. Kingbase vs. Microsoft SQL Server vs. RethinkDB

System Properties Comparison atoti vs. Datomic vs. Kingbase vs. Microsoft SQL Server vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Microsofts flagship relational DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Object oriented DBMS

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

atoti.io

www.datomic.com

www.kingbase.com.cn

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

rethinkdb.com

Technical documentation

docs.atoti.io

docs.datomic.com

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

rethinkdb.com/docs

Developer

ActiveViam

Cognitect

BeiJing KINGBASE Information technologies inc.

Microsoft

The Linux Foundation

since July 2017

Initial release

2012

1999

1989

2009

Current release

1.0.6735, June 2023

V8.0, August 2021

SQL Server 2022, November 2022

2.4.1, August 2020

License

Commercial or Open Source

commercial

free versions available

commercial

limited edition free

commercial

restricted free version is available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Java, Clojure

C and Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Multidimensional Expressions (MDX)

Standard with numerous extensions

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

Supported programming languages

Clojure
Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Python

yes

Transaction Functions

user defined functions

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

Triggers

By using transaction functions

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

But extensive use of caching in the application peers

horizontal partitioning (by range, list and hash) and vertical partitioning

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

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

MVCC based

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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