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

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

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

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

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	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

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

arcadedb.com

boilerbay.com

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

github.com/STSSoft/STSdb4

www.timescale.com

Technical documentation

docs.arcadedb.com

boilerbay.com/infinitydb/manual

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

docs.timescale.com

Developer

Arcade Data

Boiler Bay Inc.

Alessandro Furieri

STS Soft SC

Timescale

Initial release

2021

2002

2008

2011

2017

Current release

September 2021

4.0

5.0.0, August 2020

4.0.8, September 2015

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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

Open Source

GPLv2, commercial license available

Open Source

Apache 2.0

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++

Server operating systems

All OS with a Java VM

server-less

Windows

Linux
OS X
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)

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

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

.NET Client API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

C#
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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