DBMS > Blueflood vs. Microsoft Azure AI Search vs. MonetDB vs. SQLite vs. UniData,UniVerse

System Properties Comparison Blueflood vs. Microsoft Azure AI Search vs. MonetDB vs. SQLite vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Search-as-a-service for web and mobile app development

A relational database management system that stores data in columns

Widely used embeddable, in-process RDBMS

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

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

blueflood.io

azure.microsoft.com/en-us/services/search

www.monetdb.org

www.sqlite.org

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

Technical documentation

github.com/rax-maas/blueflood/wiki

learn.microsoft.com/en-us/azure/search

www.monetdb.org/Documentation

www.sqlite.org/docs.html

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

Developer

Rackspace

Microsoft

MonetDB BV

Dwayne Richard Hipp

Rocket Software

Initial release

2013

2015

2004

2000

1985

Current release

Dec2023 (11.49), December 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X

hosted

FreeBSD
Linux
OS X
Solaris
Windows

server-less

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

predefined scheme

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

optional

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API

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

Supported programming languages

C#
Java
JavaScript
Python

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

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
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

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

yes

using Azure authentication

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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