DBMS > EJDB vs. Oracle Rdb vs. Spark SQL vs. SQL.JS vs. SwayDB

System Properties Comparison EJDB vs. Oracle Rdb vs. Spark SQL vs. SQL.JS vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

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

Port of SQLite to JavaScript

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store

Relational DBMS

Key-value store

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

github.com/Softmotions/ejdb

www.oracle.com/database/technologies/related/rdb.html

spark.apache.org/sql

sql.js.org

swaydb.simer.au

Technical documentation

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

www.oracle.com/database/technologies/related/rdb-doc.html

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

sql.js.org/documentation/index.html

Developer

Softmotions

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation

Alon Zakai

enhancements implemented by others

Simer Plaha

Initial release

2012

1984

2014

2012

2018

Current release

7.4.1.1, 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

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

Scala

JavaScript

Scala

Server operating systems

server-less

HP Open VMS

Linux
OS X
Windows

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

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

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

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

in-process shared library

JDBC
ODBC

JavaScript API

Supported programming languages

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

Java
Python
R
Scala

JavaScript

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate 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

yes, on a single node

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

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

yes

User concepts

Access control

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