DBMS > BigObject vs. Datomic vs. Microsoft SQL Server vs. TimesTen vs. Trafodion

System Properties Comparison BigObject vs. Datomic vs. Microsoft SQL Server vs. TimesTen vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

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

Microsofts flagship relational DBMS

In-Memory RDBMS compatible to Oracle

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

bigobject.io

www.datomic.com

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

www.oracle.com/database/technologies/related/timesten.html

trafodion.apache.org

Technical documentation

docs.bigobject.io

docs.datomic.com

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

docs.oracle.com/database/timesten-18.1

trafodion.apache.org/documentation.html

Developer

BigObject, Inc.

Cognitect

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Apache Software Foundation, originally developed by HP

Initial release

2015

2012

1989

1998

2014

Current release

1.0.7075, December 2023

SQL Server 2022, November 2022

11 Release 2 (11.2.2.8.0)

2.3.0, February 2019

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

C++

C++, Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

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

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC

Supported programming languages

Clojure
Java

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

C
C++
Java
PL/SQL

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Lua

yes

Transaction Functions

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

PL/SQL

Java Stored Procedures

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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

yes

by means of logfiles and checkpoints

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

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