DBMS > 4D vs. Apache Druid vs. Graphite vs. Postgres-XL vs. RocksDB

System Properties Comparison 4D vs. Apache Druid vs. Graphite vs. Postgres-XL vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.4d.com

druid.apache.org

github.com/graphite-project/graphite-web

www.postgres-xl.org

rocksdb.org

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

graphite.readthedocs.io

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

Developer

4D, Inc

Apache Software Foundation and contributors

Chris Davis

Facebook, Inc.

Initial release

1984

2012

2006

2014

since 2012, originally named StormDB

2013

Current release

v20, April 2023

29.0.1, April 2024

10 R1, October 2018

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

C++

Server operating systems

OS X
Windows

Linux
OS X
Unix

Linux
Unix

Linux
macOS

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL for querying

yes

distributed, parallel query execution

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

HTTP API
Sockets

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

yes

Concurrency

Support for concurrent manipulation of data

yes

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.

yes

User concepts

Access control

Users and groups

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

fine grained access rights according to SQL-standard

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