DBMS > JaguarDB vs. Microsoft Azure AI Search vs. MySQL vs. RRDtool vs. Solr

System Properties Comparison JaguarDB vs. Microsoft Azure AI Search vs. MySQL vs. RRDtool vs. Solr

Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

Widely used open source RDBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key-value store
Vector DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Search engine

Secondary database models

Vector DBMS

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.jaguardb.com

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

www.mysql.com

oss.oetiker.ch/rrdtool

solr.apache.org

Technical documentation

www.jaguardb.com/support.html

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

dev.mysql.com/doc

oss.oetiker.ch/rrdtool/doc

solr.apache.org/resources.html

Developer

DataJaguar, Inc.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Tobias Oetiker

Apache Software Foundation

Initial release

2015

1995

1999

2006

Current release

3.3 July 2023

8.4.0, April 2024

1.8.0, 2022

9.6.0, April 2024

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V2 and FLOSS

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

C and C++

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

HP-UX
Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

Numeric data only

yes

supports customizable data types and automatic typing

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

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

in-process shared library
Pipes

Java API
RESTful HTTP/JSON API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

by using the rrdcached daemon

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

rights management via user accounts

yes

using Azure authentication

Users with fine-grained authorization concept

no user groups or roles

yes

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