DBMS > Apache Drill vs. IBM Cloudant vs. InfinityDB vs. Ultipa

System Properties Comparison Apache Drill vs. IBM Cloudant vs. InfinityDB vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Database as a Service offering based on Apache CouchDB

A Java embedded Key-Value Store which extends the Java Map interface

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Document store
Relational DBMS

Document store

Key-value store

Graph DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

drill.apache.org

www.ibm.com/products/cloudant

boilerbay.com

www.ultipa.com

Technical documentation

drill.apache.org/docs

cloud.ibm.com/docs/Cloudant

boilerbay.com/infinitydb/manual

www.ultipa.com/document

Developer

Apache Software Foundation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Boiler Bay Inc.

Ultipa

Initial release

2012

2010

2002

2019

Current release

1.20.3, January 2023

4.0

License

Commercial or Open Source

Open Source

Apache Version 2

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

Erlang

Java

Server operating systems

Linux
OS X
Windows

hosted

All OS with a Java VM

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

Supported programming languages

C++

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

atomic operations within a document possible

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Access rights for users can be defined per database

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
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Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

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16 August 2021, ibm.com

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22 March 2014, App Developer Magazine

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