DBMS > GridGain vs. Immudb vs. Oracle Coherence vs. Yaacomo

System Properties Comparison GridGain vs. Immudb vs. Oracle Coherence vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

GridGain is an in-memory computing platform, built on Apache Ignite

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Oracles in-memory data grid solution

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.24
Rank	#295	Overall
	#42	Key-value stores

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Website

www.gridgain.com

github.com/codenotary/immudb
immudb.io

www.oracle.com/java/coherence

yaacomo.com

Technical documentation

www.gridgain.com/docs/index.html

docs.immudb.io

docs.oracle.com/en/middleware/standalone/coherence

Developer

GridGain Systems, Inc.

Codenotary

Oracle

Q2WEB GmbH

Initial release

2007

2020

2007

2009

Current release

GridGain 8.5.1

1.2.3, April 2022

14.1, August 2023

License

Commercial or Open Source

commercial, open source

Open Source

Apache Version 2.0

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++, .Net, Python, REST, SQL

Java

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

BSD
Linux
macOS
Solaris
Windows
z/OS

All OS with a Java VM

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

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

SQL-like syntax

yes

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java

Server-side scripts

Stored procedures

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

Triggers

yes (cache interceptors and events)

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Role-based access control
Security Hooks for custom implementations

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

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