DBMS > 4D vs. Kdb vs. OrigoDB vs. Solr vs. TimesTen

System Properties Comparison 4D vs. Kdb vs. OrigoDB vs. Solr vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

High performance Time Series DBMS

A fully ACID in-memory object graph database

A widely used distributed, scalable search engine based on Apache Lucene

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Document store
Object oriented DBMS

Search engine

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	7.70
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	44.28
Rank	#24	Overall
	#3	Search engines

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developer.4d.com

code.kx.com

origodb.com/docs

solr.apache.org/resources.html

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Kx Systems, a division of First Derivatives plc

Robert Friberg et al

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2000

kdb was released 2000, kdb+ in 2003

2009

under the name LiveDB

2006

1998

Current release

v20, April 2023

3.6, May 2018

9.5.0, February 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

Apache Version 2

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

Server operating systems

OS X
Windows

Linux
OS X
Solaris
Windows

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

supports customizable data types and automatic typing

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

can be achieved using .NET

yes

Secondary indexes

yes

table attribute 'grouped'

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (q)

Solr Parallel SQL Interface

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

.NET Client API
HTTP API
LINQ

Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

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

.Net

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java plugins

PL/SQL

Triggers

yes

with views

yes

Domain Events

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by means of logfiles and checkpoints

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

rights management via user accounts

Role based authorization

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...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

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
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Turbocharging the Engine: KX Unleashes AI-First Transformation with kdb+
28 February 2024, Business Wire

Introducing Amazon FinSpace with Managed kdb Insights, a fully managed analytics engine, commonly used by capital ...
18 May 2023, AWS Blog

KX ANNOUNCES KDB INSIGHTS AS FULLY MANAGED SERVICE ON AMAZON FINSPACE
18 May 2023, PR Newswire

McLaren Applied and KX partner to enhance ATLAS software analytics capabilities
9 August 2023, Professional Motorsport World

KX Brings the Power and Performance of kdb+ to Python Developers with PyKX
7 June 2023, Datanami

provided by Google News

Closing Bell: Solar Alliance Energy Inc flat on Monday (SOLR)
23 April 2024, The Globe and Mail

SOLR-led walkout demands better conditions for Compass workers
27 February 2024, Daily Northwestern

Long Term Trading Analysis for (SOLR)
28 March 2024, Stock Traders Daily

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

SOLR hosts teach-in of labor movements at Northwestern
28 January 2024, Daily Northwestern

provided by Google News

In-memory databases with Emulex Gen 7
25 October 2023, Broadcom Inc.

provided by Google News

Share this page