DBMS > AgensGraph vs. GridGain vs. Sequoiadb vs. SwayDB

System Properties Comparison AgensGraph vs. GridGain vs. Sequoiadb vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

NewSQL database with distributed OLTP and SQL

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Graph DBMS
Relational DBMS

Key-value store
Relational DBMS

Document store
Relational DBMS

Key-value store

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

bitnine.net/agensgraph

www.gridgain.com

www.sequoiadb.com

swaydb.simer.au

Technical documentation

bitnine.net/documentation

www.gridgain.com/docs/index.html

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

Developer

Bitnine Global Inc.

GridGain Systems, Inc.

Sequoiadb Ltd.

Simer Plaha

Initial release

2016

2007

2013

2018

Current release

2.1, December 2018

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

GNU Affero GPL V3.0

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++, .Net

C++

Scala

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

APIs and other access methods

Cypher Query Language
JDBC

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

proprietary protocol using JSON

Supported programming languages

C
Java
JavaScript
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

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

JavaScript

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

Source-replica replication

none

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

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

Atomic execution of operations

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

Security Hooks for custom implementations

simple password-based access control

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