DBMS > PouchDB vs. SAP HANA vs. STSdb vs. TimesTen vs. Vitess

System Properties Comparison PouchDB vs. SAP HANA vs. STSdb vs. TimesTen vs. Vitess

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS with an API inspired by CouchDB

In-memory, column based data store. Available as appliance or cloud service

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS

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

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

pouchdb.com

www.sap.com/products/hana.html

github.com/STSSoft/STSdb4

www.oracle.com/database/technologies/related/timesten.html

vitess.io

Technical documentation

pouchdb.com/guides

help.sap.com/hana

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Apache Software Foundation

SAP

STS Soft SC

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

The Linux Foundation, PlanetScale

Initial release

2012

2010

2011

1998

2013

Current release

7.1.1, June 2019

2.0 SPS07 (April 4, 2023), April 2023

4.0.8, September 2015

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

Open Source

commercial

Open Source

GPLv2, commercial license available

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Appliance or cloud-service

Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

.NET Client API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

JavaScript

C#
Java

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

SQLScript, R

PL/SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

by means of logfiles and checkpoints

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

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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