DBMS > EJDB vs. GeoMesa vs. Lovefield vs. Microsoft Azure Synapse Analytics

System Properties Comparison EJDB vs. GeoMesa vs. Lovefield vs. Microsoft Azure Synapse Analytics

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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.

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Document store

Spatial DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

github.com/Softmotions/ejdb

www.geomesa.org

google.github.io/lovefield

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

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

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/azure/synapse-analytics

Developer

Softmotions

CCRi and others

Google

Microsoft

Initial release

2012

2014

2016

Current release

5.0.0, May 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache License 2.0

Open Source

Apache 2.0

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

JavaScript

C++

Server operating systems

server-less

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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-like query language

via JavaScript builder pattern

yes

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

Supported programming languages

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

JavaScript

C#
Java
PHP

Server-side scripts

Stored procedures

Transact SQL

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

none

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

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

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

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

yes

depending on the DBMS used for storage

yes

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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