DBMS > 4D vs. eXtremeDB vs. Memgraph vs. RocksDB vs. Solr

System Properties Comparison 4D vs. eXtremeDB vs. Memgraph vs. RocksDB vs. Solr

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

An open source graph database built for real-time streaming and compatible with Neo4j

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Graph DBMS

Key-value store

Search engine

Secondary database models

Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

Technical documentation

developer.4d.com

www.mcobject.com/docs/extremedb.htm

memgraph.com/docs

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

Social network pages

Developer

4D, Inc

McObject

Memgraph Ltd

Facebook, Inc.

Apache Software Foundation

Initial release

1984

2001

2017

2013

2006

Current release

v20, April 2023

8.2, 2021

8.11.4, April 2024

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

BSD

Open Source

Apache Version 2

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++

C++

Java

Server operating systems

OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free and schema-optional

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

close to SQL 92

yes

with the option: eXtremeSQL

Solr Parallel SQL Interface

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

Bolt protocol
Cypher query language

C++ API
Java API

Java API
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

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

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

by defining events

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Sharding

dynamic graph partitioning

horizontal partitioning

Sharding

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 using RAFT

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Users, roles and permissions

yes

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Memgraph directly connects to your streaming infrastructure so you and your team...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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You can check out our pricing model and licenses on the company website .
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.