DBMS > Apache Druid vs. DataFS vs. FeatureBase vs. SpaceTime

System Properties Comparison Apache Druid vs. DataFS vs. FeatureBase vs. SpaceTime

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Editorial information provided by DB-Engines

Name

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.

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS
Time Series DBMS

Object oriented DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Graph DBMS

Relational DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Website

druid.apache.org

newdatabase.com

www.featurebase.com

www.mireo.com/spacetime

Technical documentation

druid.apache.org/docs/latest/design

dev.mobiland.com/Overview.xsp

docs.featurebase.com

Developer

Apache Software Foundation and contributors

Mobiland AG

Molecula and Pilosa Open Source Contributors

Mireo

Initial release

2012

2018

2017

2020

Current release

30.0.0, June 2024

1.1.263, October 2022

2022, May 2022

License

Commercial or Open Source

Open Source

Apache license v2

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++

Server operating systems

Linux
OS X
Unix

Windows

Linux
macOS

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL queries

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
VB.Net

Java
Python

C#
C++
Python

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Proprietary Sharding system

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

yes

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