DBMS > Blueflood vs. Drizzle vs. MonetDB vs. XTDB

System Properties Comparison Blueflood vs. Drizzle vs. MonetDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A relational database management system that stores data in columns

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

blueflood.io

www.monetdb.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.monetdb.org/Documentation

www.xtdb.com/docs

Developer

Rackspace

Drizzle project, originally started by Brian Aker

MonetDB BV

Juxt Ltd.

Initial release

2013

2008

2004

2019

Current release

7.2.4, September 2012

Dec2023 (11.49), December 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

Mozilla Public License 2.0

Open Source

MIT 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

Java

C++

Clojure

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

with proprietary extensions

yes

SQL 2003 with some extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

JDBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST
JDBC

Supported programming languages

C
C++
Java
PHP

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

Clojure
Java

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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