DBMS > Alibaba Cloud TSDB vs. Elasticsearch vs. SQLite vs. TimescaleDB vs. Transwarp KunDB

System Properties Comparison Alibaba Cloud TSDB vs. Elasticsearch vs. SQLite vs. TimescaleDB vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Widely used embeddable, in-process RDBMS

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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	135.35
Rank	#7	Overall
	#1	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

www.elastic.co/elasticsearch

www.sqlite.org

www.timescale.com

www.transwarp.cn/en/product/kundb

Technical documentation

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

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.sqlite.org/docs.html

docs.timescale.com

Developer

Alibaba

Elastic

Dwayne Richard Hipp

Timescale

Transwarp

Initial release

2010

2000

2017

Current release

8.6, January 2023

3.45.3 (15 April 2024), April 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

Public Domain

Open Source

Apache 2.0

commercial

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

All OS with a Java VM

server-less

Linux
OS X
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

HTTP REST

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
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

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

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, across time and space (hash partitioning) attributes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

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

via file-system locks

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.

Memcached and Redis integration

yes

User concepts

Access control

Access managed on TSDB instance level

fine grained access rights according to SQL-standard

yes

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