DBMS > BigObject vs. BoltDB vs. Linter vs. Microsoft Azure AI Search vs. OpenQM

System Properties Comparison BigObject vs. BoltDB vs. Linter vs. Microsoft Azure AI Search vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embedded key-value store for Go.

RDBMS for high security requirements

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Spatial DBMS

Vector DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

bigobject.io

github.com/boltdb/bolt

linter.ru

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.bigobject.io

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

Developer

BigObject, Inc.

relex.ru

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2015

2013

1990

2015

1993

Current release

3.4-12

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

commercial

Open Source

GPLv2, extended commercial license available

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 and C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

BSD
Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C#
Java
JavaScript
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

yes

using Azure authentication

Access rights can be defined down to the item level

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