DBMS > Alibaba Cloud Table Store vs. Amazon SimpleDB vs. jBASE vs. SQLite vs. TimescaleDB

System Properties Comparison Alibaba Cloud Table Store vs. Amazon SimpleDB vs. jBASE vs. SQLite vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

A robust multi-value DBMS comprising development tools and middleware

Widely used embeddable, in-process RDBMS

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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/simpledb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.sqlite.org

www.timescale.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/simpledb

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.sqlite.org/docs.html

docs.timescale.com

Developer

Alibaba

Amazon

Rocket Software (formerly Zumasys)

Dwayne Richard Hipp

Timescale

Initial release

2016

2007

1991

2000

2017

Current release

5.7

3.46.0 (23 May 2024), May 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

Server operating systems

hosted

AIX
Linux
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

optional

yes

not rigid because of 'dynamic typing' concept.

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

Embedded SQL for jBASE in BASIC

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based 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
Python

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

.Net
Basic
Jabbascript
Java

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding must be implemented in the application

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

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 based on subaccounts and tokens

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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