DBMS > Apache Impala vs. Blueflood vs. H2 vs. HyperSQL vs. IBM Cloudant

System Properties Comparison Apache Impala vs. Blueflood vs. H2 vs. HyperSQL vs. IBM Cloudant

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on Cassandra

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Database as a Service offering based on Apache CouchDB

Primary database model

Secondary database models

Document store

Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Website

www.ibm.com/products/cloudant

Technical documentation

impala.apache.org/impala-docs.html

github.com/rax-maas/blueflood/wiki

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Rackspace

Thomas Mueller

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2013

2005

2001

2010

Current release

4.1.0, June 2022

2.2.220, July 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

based on BSD license

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++

Java

Erlang

Server operating systems

Linux

Linux
OS X

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Data scheme

yes

predefined scheme

yes

schema-free

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Java

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures and User-Defined Functions

Java, SQL

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

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HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google 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

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