DBMS > GeoMesa vs. Google Cloud Datastore vs. Graph Engine vs. Microsoft Azure SQL Database vs. Sadas Engine

System Properties Comparison GeoMesa vs. Google Cloud Datastore vs. Graph Engine vs. Microsoft Azure SQL Database vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Database as a Service offering with high compatibility to Microsoft SQL Server

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Spatial DBMS

Document store

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.geomesa.org

cloud.google.com/datastore

www.graphengine.io

azure.microsoft.com/en-us/products/azure-sql/database

www.sadasengine.com

Technical documentation

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

cloud.google.com/datastore/docs

www.graphengine.io/docs/manual

docs.microsoft.com/en-us/azure/azure-sql

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

CCRi and others

Google

Microsoft

SADAS s.r.l.

Initial release

2014

2008

2010

2006

Current release

5.0.0, May 2024

V12

8.0

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MIT License

commercial

free trial version available

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

.NET and C

C++

Server operating systems

hosted

.NET

hosted

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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-like query language (GQL)

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
F#
Visual Basic

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

using Google App Engine

yes

Transact SQL

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication using Paxos

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

managed by 'Learn by Usage'

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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