DBMS > Heroic vs. ITTIA vs. MonetDB vs. SWC-DB

System Properties Comparison Heroic vs. ITTIA vs. MonetDB vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

A relational database management system that stores data in columns

A high performance, scalable Wide Column DBMS

Primary database model

Time Series DBMS

Relational DBMS

Wide column store

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/spotify/heroic

www.ittia.com

www.monetdb.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

spotify.github.io/heroic

www.monetdb.org/Documentation

Developer

Spotify

ITTIA L.L.C.

MonetDB BV

Alex Kashirin

Initial release

2014

2007

2004

2020

Current release

8.7

Dec2023 (11.49), December 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL V3

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

Java

C and C++

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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 2003 with some extensions

SQL-like query language

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Proprietary protocol
Thrift

Supported programming languages

C
C++
JavaScript (Node.js)
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C++

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Database file passwords

fine grained access rights according to SQL-standard

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