DBMS > GridDB vs. Hazelcast vs. SAP HANA vs. UniData,UniVerse vs. YottaDB

System Properties Comparison GridDB vs. Hazelcast vs. SAP HANA vs. UniData,UniVerse vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

In-memory, column based data store. Available as appliance or cloud service

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Key-value store
Relational DBMS

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

griddb.net

hazelcast.com

www.sap.com/products/hana.html

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

yottadb.com

Technical documentation

docs.griddb.net

hazelcast.org/imdg/docs

help.sap.com/hana

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

yottadb.com/resources/documentation

Developer

Toshiba Corporation

Hazelcast

SAP

Rocket Software

YottaDB, LLC

Initial release

2013

2008

2010

1985

2001

Current release

5.1, August 2022

5.3.6, November 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

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

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux

All OS with a Java VM

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Java API

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
Basic

U2 Basic
C
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

SQLScript, R

yes

Triggers

yes

Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

one or two-phase-commit; repeatable reads; read commited

ACID

configurable

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

Role-based access control

yes

Access rights according to SQL-standard and operating system based

Users and groups based on OS-security mechanisms

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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