DBMS > EJDB vs. Firebase Realtime Database vs. Kdb vs. SQLite vs. Warp 10

System Properties Comparison EJDB vs. Firebase Realtime Database vs. Kdb vs. SQLite vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

High performance Time Series DBMS

Widely used embeddable, in-process RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

github.com/Softmotions/ejdb

firebase.google.com/products/realtime-database

kx.com

www.sqlite.org

www.warp10.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

firebase.google.com/docs/database

code.kx.com

www.sqlite.org/docs.html

www.warp10.io/content/02_Getting_started

Developer

Softmotions

Google

acquired by Google 2014

Kx Systems, a division of First Derivatives plc

Dwayne Richard Hipp

SenX

Initial release

2012

2000

kdb was released 2000, kdb+ in 2003

2000

2015

Current release

3.6, May 2018

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

free 32-bit version

Open Source

Public Domain

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

server-less

hosted

Linux
OS X
Solaris
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

SQL-like query language (q)

yes

SQL-92 is not fully supported

APIs and other access methods

in-process shared library

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP API
Jupyter
WebSocket

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
JavaScript
Objective-C

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

yes

WarpScript

Triggers

Callbacks are triggered when data changes

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

selectable replication factor

based on HBase

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

via file-system locks

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

yes, based on authentication and database rules

rights management via user accounts

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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.