DBMS > Apache Drill vs. Heroic vs. IBM Cloudant vs. YottaDB

System Properties Comparison Apache Drill vs. Heroic vs. IBM Cloudant vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Database as a Service offering based on Apache CouchDB

A fast and solid embedded Key-value store

Primary database model

Document store
Relational DBMS

Time Series DBMS

Document store

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

drill.apache.org

github.com/spotify/heroic

www.ibm.com/products/cloudant

yottadb.com

Technical documentation

drill.apache.org/docs

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

yottadb.com/resources/documentation

Developer

Apache Software Foundation

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

YottaDB, LLC

Initial release

2012

2014

2010

2001

Current release

1.20.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0

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

Java

Erlang

Server operating systems

Linux
OS X
Windows

hosted

Docker
Linux

Data scheme

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

via Elasticsearch

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

by using the Octo plugin

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

RESTful HTTP/JSON API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C++

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users can be defined per database

Users and groups based on OS-security mechanisms

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
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31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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