DBMS > Cachelot.io vs. HEAVY.AI vs. IBM Cloudant vs. Ingres

System Properties Comparison Cachelot.io vs. HEAVY.AI vs. IBM Cloudant vs. Ingres

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Database as a Service offering based on Apache CouchDB

Well established RDBMS

Primary database model

Secondary database models

Spatial DBMS

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

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

cachelot.io

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/cloudant

www.actian.com/databases/ingres

Technical documentation

docs.heavy.ai

cloud.ibm.com/docs/Cloudant

docs.actian.com/ingres

Developer

HEAVY.AI, Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Actian Corporation

Initial release

2015

2016

2010

1974

originally developed at University Berkely in early 1970s

Current release

5.10, January 2022

11.2, May 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2; enterprise edition available

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++

C++ and CUDA

Erlang

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

JDBC
ODBC
Thrift
Vega

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication
Source-replica replication

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

MVCC

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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