DBMS > Alibaba Cloud TSDB vs. Graphite vs. SQLite vs. TimescaleDB vs. Vitess

System Properties Comparison Alibaba Cloud TSDB vs. Graphite vs. SQLite vs. TimescaleDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Widely used embeddable, in-process RDBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

github.com/graphite-project/graphite-web

www.sqlite.org

www.timescale.com

vitess.io

Technical documentation

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

graphite.readthedocs.io

www.sqlite.org/docs.html

docs.timescale.com

vitess.io/docs

Developer

Alibaba

Chris Davis

Dwayne Richard Hipp

Timescale

The Linux Foundation, PlanetScale

Initial release

2006

2000

2017

2013

Current release

3.45.3 (15 April 2024), April 2024

2.15.0, May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses available

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

Python

Server operating systems

hosted

Linux
Unix

server-less

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

Numeric data and Strings

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

yes

with proprietary extensions

APIs and other access methods

HTTP REST

HTTP API
Sockets

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with hot standby and reads on replicas

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

via file-system locks

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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