DBMS > Heroic vs. IBM Cloudant vs. TDSQL for MySQL vs. ToroDB

System Properties Comparison Heroic vs. IBM Cloudant vs. TDSQL for MySQL vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Database as a Service offering based on Apache CouchDB

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.tencentcloud.com/products/dcdb

github.com/torodb/server

Technical documentation

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

www.tencentcloud.com/document/product/1042

Developer

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Tencent

8Kdata

Initial release

2014

2010

2013

2016

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

Java

Server operating systems

hosted

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic 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.

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

Access rights for users and roles

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