DBMS > Brytlyt vs. Citus vs. Microsoft Azure AI Search vs. SQLite vs. Tibero

System Properties Comparison Brytlyt vs. Citus vs. Microsoft Azure AI Search vs. SQLite vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Widely used embeddable, in-process RDBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store

Vector DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

brytlyt.io

www.citusdata.com

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

www.sqlite.org

us.tmaxsoft.com/products/tibero

Technical documentation

docs.brytlyt.io

docs.citusdata.com

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

www.sqlite.org/docs.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Brytlyt

Microsoft

Dwayne Richard Hipp

TmaxSoft

Initial release

2016

2010

2015

2000

2003

Current release

5.0, August 2023

8.1, December 2018

3.46.0 (23 May 2024), May 2024

6, April 2015

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++ and CUDA

C and Assembler

Server operating systems

Linux
OS X
Windows

Linux

hosted

server-less

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

specific XML-type available, but no XML query functionality.

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript
Python

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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