DBMS > Amazon SimpleDB vs. Hawkular Metrics vs. SQLite vs. TDengine vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. Hawkular Metrics vs. SQLite vs. TDengine vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Widely used embeddable, in-process RDBMS

Time Series DBMS and big data platform

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

Primary database model

Secondary database models

Relational DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/simpledb

www.hawkular.org

www.sqlite.org

github.com/taosdata/TDengine
tdengine.com

www.timescale.com

Technical documentation

docs.aws.amazon.com/simpledb

www.hawkular.org/hawkular-metrics/docs/user-guide

www.sqlite.org/docs.html

docs.tdengine.com

docs.timescale.com

Developer

Amazon

Community supported by Red Hat

Dwayne Richard Hipp

TDEngine, previously Taos Data

Timescale

Initial release

2007

2014

2000

2019

2017

Current release

3.45.3 (15 April 2024), April 2024

3.0, August 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

AGPL V3, also commercial editions available

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

Java

Server operating systems

hosted

Linux
OS X
Windows

server-less

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

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

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 columns are indexed automatically

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

Standard SQL with extensions for time-series applications

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API

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

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Java
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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
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

Triggers

yes

via Hawkular Alerting

yes

yes, via alarm monitoring

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

based on Cassandra

none

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
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