DBMS > ArangoDB vs. GridGain vs. SiriDB

System Properties Comparison ArangoDB vs. GridGain vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

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

Open Source Time Series DBMS

Primary database model

Document store
Graph DBMS
Key-value store
Search engine

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

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

Score	2.96
Rank	#89	Overall
	#15	Document stores
	#5	Graph DBMS
	#13	Key-value stores
	#10	Search engines

Score	1.37
Rank	#154	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#70	Relational DBMS

Score	0.04
Rank	#361	Overall
	#38	Time Series DBMS

Website

arangodb.com

www.gridgain.com

siridb.com

Technical documentation

docs.arangodb.com

www.gridgain.com/docs/index.html

docs.siridb.com

Developer

ArangoDB Inc.

GridGain Systems, Inc.

Cesbit

Initial release

2012

2007

2017

Current release

3.11.5, November 2023

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial license (Enterprise) available

commercial, open source

Open Source

MIT License

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

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

schema-free

automatically recognizes schema within a collection

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

Numeric data

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

APIs and other access methods

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

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

HTTP API

Supported programming languages

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

JavaScript

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

since version 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with configurable replication factor

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

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

yes

Role-based access control
Security Hooks for custom implementations

simple rights management via user accounts

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More resources

DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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Recent citations in the news

Graph Database Market Size is Projected to Reach USD 14.53
22 August 2024, GlobeNewswire

ArangoDB Unveils ArangoGraph Insights Platform
4 October 2022, Datanami

ArangoDB 3.5 update improves multi-model database platform
22 August 2019, TechTarget

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

Multimodel database company ArangoDB lands $10M in funding
14 March 2019, SiliconANGLE News

provided by Google News

GridGain in-memory data and generative AI
10 May 2024, Blocks and Files

GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideBIGDATA

Nikita Ivanov - GridGain Systems, Founder and CTO
24 April 2018, TechTarget

GridGain In-Memory Data Fabric Becomes Apache Ignite
9 April 2015, Linux.com

This little fish has teeth: GridGain takes on Oracle, SAP with its in-memory computing tech
15 October 2013, VentureBeat

provided by Google News

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