DBMS > BigObject vs. EJDB vs. Greenplum vs. HBase vs. Sequoiadb

System Properties Comparison BigObject vs. EJDB vs. Greenplum vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Wide-column store based on Apache Hadoop and on concepts of BigTable

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Wide column store

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

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

Website

bigobject.io

github.com/Softmotions/ejdb

greenplum.org

hbase.apache.org

www.sequoiadb.com

Technical documentation

docs.bigobject.io

github.com/Softmotions/ejdb/blob/master/README.md

docs.greenplum.org

hbase.apache.org/book.html

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

Developer

BigObject, Inc.

Softmotions

Pivotal Software Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Sequoiadb Ltd.

Initial release

2015

2012

2005

2008

2013

Current release

7.0.0, September 2023

2.3.4, January 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Apache version 2

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

Java

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)

server-less

Linux

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

yes

schema-free

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

options to bring your own types, AVRO

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

in-process shared library

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

proprietary protocol using JSON

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
Java
Perl
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple password-based access control

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