DBMS > Apache Pinot vs. Microsoft SQL Server vs. PouchDB vs. SpaceTime vs. Sphinx

System Properties Comparison Apache Pinot vs. Microsoft SQL Server vs. PouchDB vs. SpaceTime vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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Trend Chart

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

pinot.apache.org

www.microsoft.com/en-us/sql-server

pouchdb.com

www.mireo.com/spacetime

sphinxsearch.com

Technical documentation

docs.pinot.apache.org

learn.microsoft.com/en-US/sql/sql-server

pouchdb.com/guides

sphinxsearch.com/docs

Developer

Apache Software Foundation and contributors

Microsoft

Apache Software Foundation

Mireo

Sphinx Technologies Inc.

Initial release

2015

1989

2012

2020

2001

Current release

1.0.0, September 2023

SQL Server 2022, November 2022

7.1.1, June 2019

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

JavaScript

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
Windows

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

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

via views

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

A subset of ANSI SQL is implemented

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API

Proprietary protocol

Supported programming languages

Go
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript

C#
C++
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

with a proxy-based framework, named couchdb-lounge

Fixed-grid hypercubes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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