DBMS > Apache Impala vs. Heroic vs. IBM Cloudant vs. openGauss

System Properties Comparison Apache Impala vs. Heroic vs. IBM Cloudant vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Database as a Service offering based on Apache CouchDB

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Secondary database models

Document store

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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Website

impala.apache.org

github.com/spotify/heroic

www.ibm.com/products/cloudant

gitee.com/opengauss
opengauss.org

Technical documentation

impala.apache.org/impala-docs.html

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Huawei and openGauss community

Initial release

2013

2014

2010

2019

Current release

4.1.0, June 2022

3.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

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

C, C++, Java

Server operating systems

Linux

hosted

Linux

Data scheme

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica 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

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

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More resources

Recent citations in the news

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

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