DBMS > LevelDB vs. OpenTSDB vs. Riak TS vs. Stardog vs. TDengine

System Properties Comparison LevelDB vs. OpenTSDB vs. Riak TS vs. Stardog vs. TDengine

Editorial information provided by DB-Engines

Name

Description

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

Scalable Time Series DBMS based on HBase

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Time Series DBMS and big data platform

Primary database model

Secondary database models

Relational DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

github.com/google/leveldb

opentsdb.net

www.stardog.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

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

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

www.tiot.jp/riak-docs/riak/ts/latest

docs.stardog.com

docs.tdengine.com

Developer

Google

currently maintained by Yahoo and other contributors

Open Source, formerly Basho Technologies

Stardog-Union

TDEngine, previously Taos Data

Initial release

2011

2015

2010

2019

Current release

1.23, February 2021

3.0.0, September 2022

7.3.0, May 2020

3.0, August 2022

License

Commercial or Open Source

Open Source

BSD

Open Source

LGPL

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

AGPL V3, also commercial editions 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++

Java

Erlang

Java

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Windows

Linux
OS X

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

Secondary indexes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes, limited

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP API
Telnet API

HTTP API
Native Erlang Interface

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
RESTful HTTP API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Erlang
Go
Java
Python
R
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

selectable replication factor

Multi-source replication in HA-Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

links between datasets can be stored

yes

relationships in graphs

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

with automatic compression on writes

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

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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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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