DBMS > Badger vs. Lovefield vs. Sadas Engine vs. Trafodion

System Properties Comparison Badger vs. Lovefield vs. Sadas Engine vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable relational database for web apps written in pure JavaScript

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

github.com/dgraph-io/badger

google.github.io/lovefield

www.sadasengine.com

trafodion.apache.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/google/lovefield/blob/master/docs/spec_index.md

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

trafodion.apache.org/documentation.html

Developer

DGraph Labs

Google

SADAS s.r.l.

Apache Software Foundation, originally developed by HP

Initial release

2017

2014

2006

2014

Current release

2.1.12, February 2017

8.0

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Apache 2.0

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

JavaScript

C++

C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

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

tested with Chrome, Firefox, IE, Safari

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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