DBMS > 4D vs. Geode vs. Kdb vs. Solr vs. SpaceTime

System Properties Comparison 4D vs. Geode vs. Kdb vs. Solr vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

High performance Time Series DBMS

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

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

Primary database model

Relational DBMS

Key-value store

Time Series DBMS
Vector DBMS

Search engine

Spatial DBMS

Secondary database models

Relational DBMS

Spatial DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

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

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.mireo.com/spacetime

Technical documentation

developer.4d.com

geode.apache.org/docs

code.kx.com

solr.apache.org/resources.html

Developer

4D, Inc

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Kx Systems, a division of First Derivatives plc

Apache Software Foundation

Mireo

Initial release

1984

2002

2000

kdb was released 2000, kdb+ in 2003

2006

2020

Current release

v20, April 2023

1.1, February 2017

3.6, May 2018

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

C++

Server operating systems

OS X
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Solaris
Windows

All OS with a Java VM

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

Linux

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

table attribute 'grouped'

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (OQL)

SQL-like query language (q)

Solr Parallel SQL Interface

A subset of ANSI SQL is implemented

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Java Client API
Memcached protocol
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

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

C#
C++
Python

Server-side scripts

Stored procedures

yes

user defined functions

Java plugins

Triggers

yes

Cache Event Listeners

yes

with views

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Real-time block device replication (DRBD)

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

optimistic locking

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

Users and groups

Access rights per client and object definable

rights management via user accounts

yes

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

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