DBMS > gStore vs. LevelDB vs. OpenTSDB vs. TimesTen

System Properties Comparison gStore vs. LevelDB vs. OpenTSDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Scalable Time Series DBMS based on HBase

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

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

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

en.gstore.cn

github.com/google/leveldb

opentsdb.net

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

Technical documentation

en.gstore.cn/#/enDocs

github.com/google/leveldb/blob/main/doc/index.md

opentsdb.net/docs/build/html/index.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Google

currently maintained by Yahoo and other contributors

Oracle

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

Initial release

2016

2011

1998

Current release

1.2, November 2023

1.23, February 2021

Release 22.1

License

Commercial or Open Source

Open Source

BSD

Open Source

BSD

Open Source

LGPL

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

C++

Java

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
SPARQL 1.1

HTTP API
Telnet API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Erlang
Go
Java
Python
R
Ruby

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

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

based on HBase

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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

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