DBMS > Derby vs. Graphite vs. Postgres-XL vs. TimesTen

System Properties Comparison Derby vs. Graphite vs. Postgres-XL vs. TimesTen

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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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

db.apache.org/derby

github.com/graphite-project/graphite-web

www.postgres-xl.org

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

Technical documentation

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

graphite.readthedocs.io

www.postgres-xl.org/documentation

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Chris Davis

Oracle, TimesTen Performance Software, HP

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

Initial release

1997

2006

2014

since 2012, originally named StormDB

1998

Current release

10.17.1.0, November 2023

10 R1, October 2018

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Mozilla public license

commercial

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

Python

Server operating systems

All OS with a Java VM

Linux
Unix

Linux
macOS

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

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC

HTTP API
Sockets

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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