DBMS > Apache Druid vs. DataFS vs. Drizzle vs. GridGain vs. LeanXcale

System Properties Comparison Apache Druid vs. DataFS vs. Drizzle vs. GridGain vs. LeanXcale

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

GridGain is an in-memory computing platform, built on Apache Ignite

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Relational DBMS
Time Series DBMS

Object oriented DBMS

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Graph DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

dev.mobiland.com/Overview.xsp

www.gridgain.com/docs/index.html

Developer

Apache Software Foundation and contributors

Mobiland AG

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

LeanXcale

Initial release

2012

2018

2008

2007

2015

Current release

29.0.1, April 2024

1.1.263, October 2022

7.2.4, September 2012

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

GNU GPL

commercial

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++

Java, C++, .Net

Server operating systems

Linux
OS X
Unix

Windows

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

yes

through Apache Derby

APIs and other access methods

JDBC
RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

C
Java
Scala

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

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

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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