DBMS > Kdb vs. ObjectBox vs. Postgres-XL vs. RocksDB vs. TimescaleDB

System Properties Comparison Kdb vs. ObjectBox vs. Postgres-XL vs. RocksDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

High performance Time Series DBMS

Extremely fast embedded database for small devices, IoT and Mobile

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

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

Time Series DBMS

Document store
Spatial DBMS

Relational DBMS

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

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

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

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

code.kx.com

docs.objectbox.io

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Kx Systems, a division of First Derivatives plc

ObjectBox Limited

Facebook, Inc.

Timescale

Initial release

2000

kdb was released 2000, kdb+ in 2003

2017

2014

since 2012, originally named StormDB

2013

2017

Current release

3.6, May 2018

10 R1, October 2018

8.11.4, April 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Apache License 2.0

Open Source

Mozilla public license

Open Source

BSD

Open Source

Apache 2.0

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

C and C++

C++

Server operating systems

Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

yes

distributed, parallel query execution

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Proprietary native API

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

C++ API
Java API

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

Supported programming languages

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

online/offline synchronization between client and server

yes

Source-replica replication with hot standby and reads on replicas

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

MVCC

yes

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

rights management via user accounts

yes

fine grained access rights according to SQL-standard

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...
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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...
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Licensing and pricing models

upon request
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News

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

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