DBMS > Alibaba Cloud TSDB vs. Microsoft Azure Table Storage vs. SQLite vs. TimescaleDB vs. Titan

System Properties Comparison Alibaba Cloud TSDB vs. Microsoft Azure Table Storage vs. SQLite vs. TimescaleDB vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used embeddable, in-process RDBMS

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/hitsdb

azure.microsoft.com/en-us/services/storage/tables

www.sqlite.org

www.timescale.com

github.com/thinkaurelius/titan

Technical documentation

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

www.sqlite.org/docs.html

docs.timescale.com

github.com/thinkaurelius/titan/wiki

Developer

Alibaba

Microsoft

Dwayne Richard Hipp

Timescale

Aurelius, owned by DataStax

Initial release

2012

2000

2017

2012

Current release

3.45.3 (15 April 2024), April 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

Open Source

Apache 2.0

Open Source

Apache license, version 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

Java

Server operating systems

hosted

server-less

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

APIs and other access methods

HTTP REST

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Clojure
Java
Python

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes, across time and space (hash partitioning) attributes

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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