DBMS > 4D vs. Drizzle vs. JanusGraph vs. TimesTen vs. VictoriaMetrics

System Properties Comparison 4D vs. Drizzle vs. JanusGraph vs. TimesTen vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Application development environment with integrated database management system

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-Memory RDBMS compatible to Oracle

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

www.4d.com

janusgraph.org

www.oracle.com/database/technologies/related/timesten.html

victoriametrics.com

Technical documentation

developer.4d.com

docs.janusgraph.org

docs.oracle.com/database/timesten-18.1

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

4D, Inc

Drizzle project, originally started by Brian Aker

Linux Foundation; originally developed as Titan by Aurelius

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

VictoriaMetrics

Initial release

1984

2008

2017

1998

2018

Current release

v20, April 2023

7.2.4, September 2012

0.6.3, February 2023

11 Release 2 (11.2.2.8.0)

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

Open Source

Apache Version 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

C++

Java

Server operating systems

OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

FreeBSD
Linux
macOS
OpenBSD

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with proprietary extensions

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

4D proprietary IDE
PHP

C
C++
Java
PHP

Clojure
Java
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

by means of logfiles and checkpoints

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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More resources

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Recent citations in the news

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