DBMS > Apache Drill vs. GeoMesa vs. Microsoft Azure Synapse Analytics vs. Realm

System Properties Comparison Apache Drill vs. GeoMesa vs. Microsoft Azure Synapse Analytics 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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Spatial DBMS

Relational DBMS

Document store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

drill.apache.org

www.geomesa.org

azure.microsoft.com/services/synapse-analytics

realm.io

Technical documentation

drill.apache.org/docs

www.geomesa.org/documentation/stable/user/index.html

docs.microsoft.com/azure/synapse-analytics

realm.io/docs

Developer

Apache Software Foundation

CCRi and others

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2012

2014

2016

2014

Current release

1.20.3, January 2023

5.0.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache License 2.0

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

Scala

C++

Server operating systems

Linux
OS X
Windows

hosted

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C++

C#
Java
PHP

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

Transact SQL

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

depending on storage layer

yes

In-Memory realm

User concepts

Access control

Depending on the underlying data source

yes

depending on the DBMS used for storage

yes

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More resources

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