DBMS > Alibaba Cloud TSDB vs. Apache IoTDB vs. RethinkDB vs. TimescaleDB vs. Typesense

System Properties Comparison Alibaba Cloud TSDB vs. Apache IoTDB vs. RethinkDB vs. TimescaleDB vs. Typesense

Editorial information provided by DB-Engines

Name

Description

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.24
Rank	#296	Overall
	#24	Time Series DBMS

Score	1.41
Rank	#151	Overall
	#14	Time Series DBMS

Score	2.52
Rank	#105	Overall
	#20	Document stores

Score	3.68
Rank	#74	Overall
	#5	Time Series DBMS

Score	0.80
Rank	#209	Overall
	#14	Search engines

Website

www.alibabacloud.com/product/hitsdb

Technical documentation

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

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

rethinkdb.com/docs

docs.timescale.com

typesense.org/docs

Developer

Alibaba

Apache Software Foundation

The Linux Foundation

since July 2017

Timescale

Initial release

2018

2009

2017

2015

Current release

1.1.0, April 2023

2.4.1, August 2020

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GPL V3

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

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

Numeric data and Strings

yes

string, binary, float, bool, date, geometry

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

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP REST

JDBC
Native API

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

RESTful HTTP API

Supported programming languages

Java

C
C#
C++
Go
Java
Python
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes

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

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

range based

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

Source-replica replication with hot standby and reads on replicas

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

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

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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