DBMS > EJDB vs. Galaxybase vs. Machbase Neo vs. Spark SQL vs. Transbase

System Properties Comparison EJDB vs. Galaxybase vs. Machbase Neo vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

Scalable, ACID-compliant native distributed parallel graph platform

TimeSeries DBMS for AIoT and BigData

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

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	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

github.com/Softmotions/ejdb

galaxybase.com

machbase.com

spark.apache.org/sql

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

Technical documentation

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

machbase.com/dbms

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

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

Developer

Softmotions

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Machbase

Apache Software Foundation

Transaction Software GmbH

Initial release

2012

2017

2013

2014

1987

Current release

Nov 20, November 2021

V8.0, August 2023

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

free test version available

Open Source

Apache 2.0

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

C and Java

Scala

C and C++

Server operating systems

server-less

Linux

Linux
macOS
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

Strong typed schema

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

SQL-like DML and DDL statements

yes

APIs and other access methods

in-process shared library

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

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

Go
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Python
R
Scala

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

Server-side scripts

Stored procedures

user defined procedures and functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

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

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

Role-based access control

simple password-based access control

fine grained access rights according to SQL-standard

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