DBMS > BigObject vs. Graph Engine vs. OpenQM vs. Sequoiadb

System Properties Comparison BigObject vs. Graph Engine vs. OpenQM vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Graph DBMS
Key-value store

Multivalue DBMS

Document store
Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

bigobject.io

www.graphengine.io

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

www.sequoiadb.com

Technical documentation

docs.bigobject.io

www.graphengine.io/docs/manual

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

BigObject, Inc.

Microsoft

Rocket Software, originally Martin Phillips

Sequoiadb Ltd.

Initial release

2015

2010

1993

2013

Current release

3.4-12

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

Open Source

GPLv2, extended commercial license available

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

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)

.NET

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

C#
C++
F#
Visual Basic

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights can be defined down to the item level

simple password-based access control

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More resources

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