DBMS > Apache Impala vs. Cubrid vs. Firebase Realtime Database vs. KeyDB

System Properties Comparison Apache Impala vs. Cubrid vs. Firebase Realtime Database vs. KeyDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Website

impala.apache.org

cubrid.com (korean)
cubrid.org (english)

firebase.google.com/products/realtime-database

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

impala.apache.org/impala-docs.html

cubrid.org/manuals

firebase.google.com/docs/database

docs.keydb.dev

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CUBRID Corporation, CUBRID Foundation

Google

acquired by Google 2014

EQ Alpha Technology Ltd.

Initial release

2013

2008

2012

2019

Current release

4.1.0, June 2022

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

BSD-3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++, Java

C++

Server operating systems

Linux

Linux
Windows

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Android
iOS
JavaScript API
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

limited functionality with using 'rules'

Lua

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

simple password-based access control and ACL

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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