DBMS > Microsoft SQL Server vs. OpenTSDB vs. PouchDB vs. UniData,UniVerse vs. Vertica

System Properties Comparison Microsoft SQL Server vs. OpenTSDB vs. PouchDB vs. UniData,UniVerse vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Scalable Time Series DBMS based on HBase

JavaScript DBMS with an API inspired by CouchDB

MultiValue database and application server with SQL mapping layer and meta database capabilities

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

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

opentsdb.net

pouchdb.com

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

www.vertica.com

Technical documentation

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

opentsdb.net/docs/build/html/index.html

pouchdb.com/guides

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

vertica.com/documentation

Developer

Microsoft

currently maintained by Yahoo and other contributors

Apache Software Foundation

Rocket Software

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1989

2011

2012

1985

2005

Current release

SQL Server 2022, November 2022

7.1.1, June 2019

12.0.3, January 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

LGPL

Open Source

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

JavaScript

C++

Server operating systems

Linux
Windows

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

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

optional

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

HTTP API
Telnet API

HTTP REST

only for PouchDB Server
JavaScript API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

JavaScript

.Net
Basic

U2 Basic
C
Java

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

Server-side scripts

Stored procedures

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

View functions in JavaScript

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

U2 Basic

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on HBase

Sharding

with a proxy-based framework, named couchdb-lounge

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

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

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

Access rights according to SQL-standard and operating system based

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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Licensing and pricing models

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