DBMS > Axibase vs. BigObject vs. EventStoreDB vs. GridDB vs. UniData,UniVerse

System Properties Comparison Axibase vs. BigObject vs. EventStoreDB vs. GridDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Analytic DBMS for real-time computations and queries

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Scalable in-memory time series database optimized for IoT and Big Data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Event Store

Time Series DBMS

Multivalue DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	2.02
Rank	#132	Overall
	#11	Time Series DBMS

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

axibase.com/docs/atsd/finance

bigobject.io

www.eventstore.com

griddb.net

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

Technical documentation

docs.bigobject.io

developers.eventstore.com

docs.griddb.net

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Axibase Corporation

BigObject, Inc.

Event Store Limited

Toshiba Corporation

Rocket Software

Initial release

2013

2015

2012

2013

1985

Current release

15585

21.2, February 2021

5.1, August 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community edition available

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

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)

Linux
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

numerical, string, blob, geometry, boolean, timestamp

optional

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

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Lua

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency within container, eventual consistency across containers

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 at container level

ACID

configurable

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 rights for users can be defined per database

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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