DBMS > FeatureBase vs. JaguarDB vs. jBASE vs. MySQL vs. Quasardb

System Properties Comparison FeatureBase vs. JaguarDB vs. jBASE vs. MySQL vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Performant, highly scalable DBMS for AI and IoT applications

A robust multi-value DBMS comprising development tools and middleware

Widely used open source RDBMS

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Multivalue DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.featurebase.com

www.jaguardb.com

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

www.mysql.com

quasar.ai

Technical documentation

docs.featurebase.com

www.jaguardb.com/support.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

dev.mysql.com/doc

doc.quasar.ai/master

Developer

Molecula and Pilosa Open Source Contributors

DataJaguar, Inc.

Rocket Software (formerly Zumasys)

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Initial release

2017

2015

1991

1995

2009

Current release

2022, May 2022

3.3 July 2023

5.7

8.4.0, April 2024

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

the server part. Clients available in other languages

C and C++

C++

Server operating systems

Linux
macOS

Linux

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL queries

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

Java
Python

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

.Net
Basic
Jabbascript
Java

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

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

rights management via user accounts

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

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