DBMS > EJDB vs. Spark SQL vs. Transbase vs. Warp 10 vs. YottaDB

System Properties Comparison EJDB vs. Spark SQL vs. Transbase vs. Warp 10 vs. YottaDB

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

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

github.com/Softmotions/ejdb

spark.apache.org/sql

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

www.warp10.io

yottadb.com

Technical documentation

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

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

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

www.warp10.io/content/02_Getting_started

yottadb.com/resources/documentation

Developer

Softmotions

Apache Software Foundation

Transaction Software GmbH

SenX

YottaDB, LLC

Initial release

2012

2014

1987

2015

2001

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

commercial

free development license

Open Source

Apache License 2.0

Open Source

AGPL 3.0

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

C and C++

Java

Server operating systems

server-less

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Docker
Linux

Data scheme

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

SQL-like DML and DDL statements

yes

by using the Octo plugin

APIs and other access methods

in-process shared library

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

Java
Python
R
Scala

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

optimistic locking

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

User concepts

Access control

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

Users and groups based on OS-security mechanisms

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