DBMS > Alibaba Cloud TSDB vs. eXtremeDB vs. Graph Engine vs. Graphite

System Properties Comparison Alibaba Cloud TSDB vs. eXtremeDB vs. Graph Engine vs. Graphite

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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

Natively in-memory DBMS with options for persistency, high-availability and clustering

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Time Series DBMS

Relational DBMS
Time Series DBMS

Graph DBMS
Key-value store

Time Series DBMS

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

Score	0.23
Rank	#300	Overall
	#24	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/hitsdb

www.mcobject.com

www.graphengine.io

github.com/graphite-project/graphite-web

Technical documentation

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

www.mcobject.com/docs/extremedb.htm

www.graphengine.io/docs/manual

graphite.readthedocs.io

Developer

Alibaba

McObject

Microsoft

Chris Davis

Initial release

2001

2010

2006

Current release

8.2, 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

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

C and C++

.NET and C

Python

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

.NET

Linux
Unix

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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

APIs and other access methods

HTTP REST

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP API

HTTP API
Sockets

Supported programming languages

Java

.Net
C
C#
C++
Java
Lua
Python
Scala

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

locking

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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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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