DBMS > EJDB vs. Spark SQL vs. SQL.JS vs. TerarkDB vs. Transbase

System Properties Comparison EJDB vs. Spark SQL vs. SQL.JS vs. TerarkDB vs. Transbase

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/Softmotions/ejdb

spark.apache.org/sql

sql.js.org

github.com/bytedance/terarkdb

www.transaction.de/en/products/transbase.html

Technical documentation

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

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

sql.js.org/documentation/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.transaction.de/en/products/transbase/features.html

Developer

Softmotions

Apache Software Foundation

Alon Zakai

enhancements implemented by others

ByteDance, originally Terark

Transaction Software GmbH

Initial release

2012

2014

2012

2016

1987

Current release

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

commercial

restricted open source version available

commercial

free development license

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

C++

C and C++

Server operating systems

server-less

Linux
OS X
Windows

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

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

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 DML and DDL statements

yes

SQL-92 is not fully supported

yes

APIs and other access methods

in-process shared library

JDBC
ODBC

JavaScript API

C++ API
Java API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

Java
Python
R
Scala

JavaScript

C++
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

yes

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the news

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News

9 Best JavaScript and TypeScript ORMs for 2024
22 March 2023, SitePoint

Execute millions of SQL statements in milliseconds in the browser with WebAssembly and Web Workers.
14 January 2017, hackernoon.com

SQLite On The Web: Absurd-sql
24 August 2021, Hackaday

In Praise Of SQLite
28 July 2022, iProgrammer

10 Low-Code Rules for Serious Coders
21 November 2022, Embedded Computing Design

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

Share this page