DBMS > GeoMesa vs. HBase vs. Microsoft Azure Synapse Analytics

System Properties Comparison GeoMesa vs. HBase vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Spatial DBMS

Wide column store

Relational DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

www.geomesa.org

hbase.apache.org

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

hbase.apache.org/book.html

docs.microsoft.com/azure/synapse-analytics

Developer

CCRi and others

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Initial release

2014

2008

2016

Current release

4.0.5, February 2024

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

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

Scala

Java

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

hosted

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

depending on storage layer

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

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More resources

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