DBMS > EJDB vs. GeoMesa vs. Microsoft Azure SQL Database vs. NSDb

System Properties Comparison EJDB vs. GeoMesa vs. Microsoft Azure SQL Database vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

github.com/Softmotions/ejdb

www.geomesa.org

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

nsdb.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

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

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

nsdb.io/Architecture

Developer

Softmotions

CCRi and others

Microsoft

Initial release

2012

2014

2010

2017

Current release

5.0.0, May 2024

V12

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2.0

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++

Java, Scala

Server operating systems

server-less

hosted

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Java
Scala

Server-side scripts

Stored procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes, with always 3 replicas available

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

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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