DBMS > Derby vs. Machbase Neo vs. OrigoDB vs. SpatiaLite vs. Splice Machine

System Properties Comparison Derby vs. Machbase Neo vs. OrigoDB vs. SpatiaLite vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

TimeSeries DBMS for AIoT and BigData

A fully ACID in-memory object graph database

Spatial extension of SQLite

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

db.apache.org/derby

machbase.com

origodb.com

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

splicemachine.com

Technical documentation

db.apache.org/derby/manuals/index.html

machbase.com/dbms

origodb.com/docs

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

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Machbase

Robert Friberg et al

Alessandro Furieri

Splice Machine

Initial release

1997

2013

2009

under the name LiveDB

2008

2014

Current release

10.17.1.0, November 2023

V8.0, August 2023

5.0.0, August 2020

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free test version available

Open Source

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

Open Source

AGPL 3.0, 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

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Linux
Windows

server-less

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

.NET Client API
HTTP API
LINQ

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Role based authorization

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

JDBC tutorial: Easy installation and setup with Apache Derby
20 December 2019, TheServerSide.com

Installing Apache Hive 3.1.2 on Windows 10 | by Hadi Fadlallah
3 May 2020, Towards Data Science

The Arrival of Java 20
21 March 2023, blogs.oracle.com

The Apache® Software Foundation Announces 18 Years of Open Source Leadership
28 March 2017, GlobeNewswire

No, Citrix did not kill CloudStack
15 September 2014, InfoWorld

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

ETL: The Silent Killer of Big Data Projects
23 July 2015, insideBIGDATA

provided by Google News

Share this page