DBMS > GeoMesa vs. Heroic vs. Microsoft Azure Synapse Analytics vs. MySQL vs. Warp 10

System Properties Comparison GeoMesa vs. Heroic vs. Microsoft Azure Synapse Analytics vs. MySQL vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

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

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

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

Widely used open source RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

www.geomesa.org

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

www.mysql.com

www.warp10.io

Technical documentation

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

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

www.warp10.io/content/02_Getting_started

Developer

CCRi and others

Spotify

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

SenX

Initial release

2014

2016

1995

2015

Current release

4.0.5, February 2024

8.3.0, January 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java

C++

C and C++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
Java
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Transact SQL

yes

proprietary syntax

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

Users with fine-grained authorization concept

no user groups or roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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