DBMS > Alibaba Cloud TSDB vs. HugeGraph vs. Prometheus vs. RRDtool

System Properties Comparison Alibaba Cloud TSDB vs. HugeGraph vs. Prometheus vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

A fast-speed and highly-scalable Graph DBMS

Open-source Time Series DBMS and monitoring system

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Time Series DBMS

Graph DBMS

Time Series DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.alibabacloud.com/product/hitsdb

github.com/hugegraph
hugegraph.apache.org

prometheus.io

oss.oetiker.ch/rrdtool

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

hugegraph.apache.org/docs

prometheus.io/docs

oss.oetiker.ch/rrdtool/doc

Developer

Alibaba

Baidu

Tobias Oetiker

Initial release

2018

2015

1999

Current release

0.9

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
macOS
Unix

Linux
Windows

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

yes

Numeric data only

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 of XML data possible

Exporting into and restoring from XML files possible

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

APIs and other access methods

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP/JSON API

in-process shared library
Pipes

Supported programming languages

Java

Groovy
Java
Python

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

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 managed on TSDB instance level

Users, roles and permissions

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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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