DBMS > Cachelot.io vs. EJDB vs. Spark SQL vs. TerarkDB vs. Transbase

System Properties Comparison Cachelot.io vs. EJDB vs. Spark SQL vs. TerarkDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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 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	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

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

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

cachelot.io

github.com/Softmotions/ejdb

spark.apache.org/sql

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

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

Developer

Softmotions

Apache Software Foundation

ByteDance, originally Terark

Transaction Software GmbH

Initial release

2015

2012

2014

2016

1987

Current release

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

GPLv2

Open Source

Apache 2.0

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

C++

Scala

C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

server-less

Linux
OS X
Windows

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

APIs and other access methods

Memcached protocol

in-process shared library

JDBC
ODBC

C++ API
Java API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

Java
Python
R
Scala

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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