DBMS > 4D vs. eXtremeDB vs. Graph Engine vs. Splice Machine

System Properties Comparison 4D vs. eXtremeDB vs. Graph Engine vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Natively in-memory DBMS with options for persistency, high-availability and clustering

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

Technical documentation

developer.4d.com

www.mcobject.com/docs/extremedb.htm

www.graphengine.io/docs/manual

splicemachine.com/how-it-works

Developer

4D, Inc

McObject

Microsoft

Splice Machine

Initial release

1984

2001

2010

2014

Current release

v20, April 2023

8.2, 2021

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

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

C and C++

.NET and C

Java

Server operating systems

OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

.NET

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with the option: eXtremeSQL

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

4D proprietary IDE
PHP

.Net
C
C#
C++
Java
Lua
Python
Scala

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Users and groups

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

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

McObject
17 November 2021, Electronic Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

Interview: Jeff Chang And Steve Graves Cover In-Memory Databases
17 December 2013, Electronic Design

Schneider Electric to collaborate with McObject
14 October 2015, Construction Week Online

provided by Google News

Trinity
30 October 2010, Microsoft

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

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 Learning
19 January 2021, PR Newswire

2021: The Year of the Feature Store
19 January 2021, Datanami

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches ML Manager Beta Program to Meet the Growing Demand for Operational AI
7 April 2019, insideBIGDATA

provided by Google News

Share this page