DBMS > IBM Cloudant vs. JaguarDB vs. JSqlDb vs. Machbase Neo vs. Spark SQL

System Properties Comparison IBM Cloudant vs. JaguarDB vs. JSqlDb vs. Machbase Neo vs. Spark SQL

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

JavaScript Query Language Database, stores JavaScript objects and primitives

TimeSeries DBMS for AIoT and BigData

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

Key-value store
Vector DBMS

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.ibm.com/products/cloudant

www.jaguardb.com

jsqldb.org (offline)

machbase.com

spark.apache.org/sql

Technical documentation

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

machbase.com/dbms

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Konrad von Backstrom

Machbase

Apache Software Foundation

Initial release

2010

2015

2018

2013

2014

Current release

3.3 July 2023

0.8, December 2018

V8.0, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

commercial

free test version available

Open Source

Apache 2.0

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

Erlang

C++

the server part. Clients available in other languages

Scala

Server operating systems

hosted

Linux

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

Access rights for users can be defined per database

rights management via user accounts

simple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Cloudant Best (and Worst) Practices — Part 1
18 March 2019, IBM

Intro to Enterprise Cloud Storage: How to Set Up a Cloudant Database
1 December 2014, Linux.com

IBM Expands Cloud Database Services with Kubernetes
26 September 2019, EnterpriseAI

IBM Code Engine and IBM Cloudant: Serverless Data and Infrastructure
16 August 2021, IBM

IBM to Purchase Cloudant Database as a service (DBaaS) Provider
22 March 2014, App Developer Magazine

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

Share this page