DBMS > BigObject vs. GBase vs. HBase vs. Ignite

System Properties Comparison BigObject vs. GBase vs. HBase vs. Ignite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An analytical database for business intelligence with large customers in China.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Wide column store

Key-value store
Relational DBMS

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Website

Technical documentation

docs.bigobject.io

hbase.apache.org/book.html

apacheignite.readme.io/docs

Developer

BigObject, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

Initial release

2015

2008

2015

Current release

GBase 8a

2.3.4, January 2021

Apache Ignite 2.6

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

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++, Java, .Net

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
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Immediate 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

Single row ACID (across millions of columns)

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

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

Security Hooks for custom implementations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

Cloudera Search Adds Search Engine Ease to Data on HDFS and Apache HBase
10 December 2023, Channel Futures

HBase: The database big data left behind
6 May 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

Apache Ignite: An Overview
6 September 2023, Open Source For You

ArcGIS and Apache Log4j Vulnerabilities
22 May 2023, Esri

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

provided by Google News

Share this page