DBMS > EsgynDB vs. GridGain vs. Sequoiadb vs. Yaacomo

System Properties Comparison EsgynDB vs. GridGain vs. Sequoiadb 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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

NewSQL database with distributed OLTP and SQL

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

Primary database model

Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

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

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

www.esgyn.cn

www.gridgain.com

www.sequoiadb.com

yaacomo.com

Technical documentation

www.gridgain.com/docs/index.html

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

Developer

Esgyn

GridGain Systems, Inc.

Sequoiadb Ltd.

Q2WEB GmbH

Initial release

2015

2007

2013

2009

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

commercial, open source

Open Source

Server: AGPL; Client: Apache V2

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

C++, Java

Java, C++, .Net, Python, REST, SQL

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows
z/OS

Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

yes

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

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

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

proprietary protocol using JSON

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

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

JavaScript

Triggers

yes (cache interceptors and 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

Multi-source replication between multi datacenters

yes (replicated cache)

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

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

fine grained access rights according to SQL-standard

Role-based access control
Security Hooks for custom implementations

simple password-based access control

fine grained access rights according to SQL-standard

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