DBMS > BigObject vs. Infobright vs. Microsoft Azure AI Search vs. TimesTen

System Properties Comparison BigObject vs. Infobright vs. Microsoft Azure AI Search vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Search-as-a-service for web and mobile app development

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

bigobject.io

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/en-us/services/search

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

Technical documentation

docs.bigobject.io

learn.microsoft.com/en-us/azure/search

docs.oracle.com/database/timesten-18.1

Developer

BigObject, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Oracle, TimesTen Performance Software, HP

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

Initial release

2015

2005

2015

1998

Current release

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free community edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

hosted

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

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.

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java
JavaScript
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Lua

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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

exploiting MySQL or PostgreSQL frontend capabilities

yes

using Azure authentication

fine grained access rights according to SQL-standard

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