DBMS > Altibase vs. Microsoft Azure Cosmos DB vs. Oracle Rdb vs. TerarkDB vs. TimesTen

System Properties Comparison Altibase vs. Microsoft Azure Cosmos DB vs. Oracle Rdb vs. TerarkDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Globally distributed, horizontally scalable, multi-model database service

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

altibase.com

azure.microsoft.com/services/cosmos-db

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

github.com/bytedance/terarkdb

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

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

learn.microsoft.com/azure/cosmos-db

www.oracle.com/database/technologies/related/rdb-doc.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Altibase

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

ByteDance, originally Terark

Oracle

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

Initial release

1999

2014

1984

2016

1998

Current release

v7.3, 2023, August 2023

7.4.1.1, 2021

Release 22.1

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

restricted open source version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

AIX
HP-UX
Linux

hosted

HP Open VMS

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

C++ API
Java API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C++
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++
Java

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

JavaScript

PL/SQL

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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