DBMS > 4D vs. Apache Druid vs. Kdb vs. TerminusDB vs. XTDB

System Properties Comparison 4D vs. Apache Druid vs. Kdb vs. TerminusDB vs. XTDB

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

High performance Time Series DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS
Vector DBMS

Graph DBMS

Document store

Secondary database models

Relational DBMS

Document store
RDF store

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	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

code.kx.com

terminusdb.github.io/terminusdb/#

www.xtdb.com/docs

Developer

4D, Inc

Apache Software Foundation and contributors

Kx Systems, a division of First Derivatives plc

DataChemist Ltd.

Juxt Ltd.

Initial release

1984

2012

2000

kdb was released 2000, kdb+ in 2003

2018

2019

Current release

v20, April 2023

29.0.1, April 2024

3.6, May 2018

11.0.0, January 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

free 32-bit version

Open Source

GPL V3

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

Prolog, Rust

Clojure

Server operating systems

OS X
Windows

Linux
OS X
Unix

Linux
OS X
Solaris
Windows

Linux

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

Data scheme

yes

schema-less columns are supported

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

yes

close to SQL 92

SQL for querying

SQL-like query language (q)

SQL-like query language (WOQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP REST
JDBC

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

JavaScript
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

horizontal partitioning

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Source-replica replication

Journaling Streams

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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 journaling

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.

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

rights management via user accounts

Role-based access control

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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