DBMS > CrateDB vs. Firebase Realtime Database vs. InterSystems Caché vs. YottaDB

System Properties Comparison CrateDB vs. Firebase Realtime Database vs. InterSystems Caché vs. YottaDB

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Distributed Database based on Lucene

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

A multi-model DBMS and application server

A fast and solid embedded Key-value store

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Relational DBMS

Document store

Relational DBMS

using the Octo plugin

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

cratedb.com

firebase.google.com/products/realtime-database

www.intersystems.com/products/cache

yottadb.com

Technical documentation

cratedb.com/docs

firebase.google.com/docs/database

docs.intersystems.com

yottadb.com/resources/documentation

Developer

Crate

Google

acquired by Google 2014

InterSystems

YottaDB, LLC

Initial release

2013

2012

1997

2001

Current release

5.8.1, August 2024

2018.1.4, May 2020

License

Commercial or Open Source

Open Source

commercial

Open Source

AGPL 3.0

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

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Docker
Linux

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

depending on used data model

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

by using the Octo plugin

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Java
JavaScript
Objective-C

C#
C++
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions (Javascript)

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

yes

ACID

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

rights management via user accounts

yes, based on authentication and database rules

Access rights for users, groups and roles

Users and groups based on OS-security mechanisms

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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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