DBMS > PouchDB vs. Prometheus vs. Splice Machine vs. STSdb

System Properties Comparison PouchDB vs. Prometheus vs. Splice Machine vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS with an API inspired by CouchDB

Open-source Time Series DBMS and monitoring system

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

pouchdb.com

prometheus.io

splicemachine.com

github.com/STSSoft/STSdb4

Technical documentation

pouchdb.com/guides

prometheus.io/docs

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Splice Machine

STS Soft SC

Initial release

2012

2015

2014

2011

Current release

7.1.1, June 2019

3.1, March 2021

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Java

Server operating systems

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

Linux
Windows

Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

yes

primitive types and user defined types (classes)

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.

Import of XML data possible

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

.NET Client API

Supported programming languages

JavaScript

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

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

by Federation

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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