DBMS > ArcadeDB vs. Ignite vs. InfinityDB vs. SpatiaLite vs. STSdb

System Properties Comparison ArcadeDB vs. Ignite vs. InfinityDB vs. SpatiaLite vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A Java embedded Key-Value Store which extends the Java Map interface

Spatial extension of SQLite

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store
Relational DBMS

Key-value store

Spatial DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

arcadedb.com

ignite.apache.org

boilerbay.com

www.gaia-gis.it/fossil/libspatialite/index

github.com/STSSoft/STSdb4

Technical documentation

docs.arcadedb.com

apacheignite.readme.io/docs

boilerbay.com/infinitydb/manual

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Arcade Data

Apache Software Foundation

Boiler Bay Inc.

Alessandro Furieri

STS Soft SC

Initial release

2021

2015

2002

2008

2011

Current release

September 2021

Apache Ignite 2.6

4.0

5.0.0, August 2020

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GPLv2, commercial license available

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++, Java, .Net

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

All OS with a Java VM

server-less

Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

primitive types and user defined types (classes)

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like query language, no joins

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

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

.NET Client API

Supported programming languages

Java

C#
C++
Java
PHP
Python
Ruby
Scala

Java

C#
Java

Server-side scripts

Stored procedures

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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

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

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

relationship in graphs

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Security Hooks for custom implementations

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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