DBMS > Apache Drill vs. Apache Ignite vs. Realm

System Properties Comparison Apache Drill vs. Apache Ignite vs. Realm

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Editorial information provided by DB-Engines

Name

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	1.82
Rank	#128	Overall
	#24	Document stores
	#60	Relational DBMS

Score	2.97
Rank	#88	Overall
	#12	Key-value stores
	#47	Relational DBMS

Score	7.12
Rank	#48	Overall
	#8	Document stores

Website

drill.apache.org

ignite.apache.org

realm.io

Technical documentation

drill.apache.org/docs

apacheignite.readme.io/docs

realm.io/docs

Developer

Apache Software Foundation

Realm, acquired by MongoDB in May 2019

Initial release

2012

2015

2014

Current release

1.20.3, January 2023

2.16.0, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java, .Net

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C++

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

runs within the applications so server-side scripts are unnecessary

Triggers

yes (cache interceptors and events)

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

yes

In-Memory realm

User concepts

Access control

Depending on the underlying data source

Security Hooks for custom implementations

yes

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More resources

DB-Engines blog posts

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Recent citations in the news

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

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

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

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

Apache Arrow Targets High Performance for Big Data Systems
17 February 2016, The Next Platform

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What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

GridGain In-Memory Data Fabric Becomes Apache Ignite
9 April 2015, Linux.com

Apache Ignite: How to Read Data From Persistent Store
3 June 2016, dzone.com

Apache Ignite: An Overview
6 September 2023, Open Source For You

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21 December 2022, Netguru

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