DBMS > Apache Impala vs. Cachelot.io vs. IBM Cloudant vs. Riak TS

System Properties Comparison Apache Impala vs. Cachelot.io vs. IBM Cloudant vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

In-memory caching system

Database as a Service offering based on Apache CouchDB

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

impala.apache.org

cachelot.io

www.ibm.com/products/cloudant

Technical documentation

impala.apache.org/impala-docs.html

cloud.ibm.com/docs/Cloudant

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Open Source, formerly Basho Technologies

Initial release

2013

2015

2010

2015

Current release

4.1.0, June 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Simplified BSD License

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++

Erlang

Server operating systems

Linux

FreeBSD
Linux
OS X

hosted

Linux
OS X

Data 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

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

yes, limited

APIs and other access methods

JDBC
ODBC

Memcached protocol

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

selectable replication factor

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

none

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

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

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More resources

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