DBMS > EsgynDB vs. Heroic vs. Lovefield vs. Trafodion

System Properties Comparison EsgynDB vs. Heroic vs. Lovefield 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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable relational database for web apps written in pure JavaScript

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

www.esgyn.cn

github.com/spotify/heroic

google.github.io/lovefield

trafodion.apache.org

Technical documentation

spotify.github.io/heroic

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

trafodion.apache.org/documentation.html

Developer

Esgyn

Spotify

Google

Apache Software Foundation, originally developed by HP

Initial release

2015

2014

Current release

2.1.12, February 2017

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

C++, Java

Java

JavaScript

C++, Java

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

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

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

User concepts

Access control

fine grained access rights according to SQL-standard

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