DBMS > EsgynDB vs. FatDB vs. ObjectBox vs. Spark SQL

System Properties Comparison EsgynDB vs. FatDB vs. ObjectBox vs. Spark SQL

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Extremely fast embedded database for small devices, IoT and Mobile

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Document store
Key-value store

Object oriented DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.esgyn.cn

objectbox.io

spark.apache.org/sql

Technical documentation

docs.objectbox.io

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Esgyn

FatCloud

ObjectBox Limited

Apache Software Foundation

Initial release

2015

2012

2017

2014

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C and C++

Scala

Server operating systems

Linux

Windows

Android
iOS
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Proprietary native API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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