DBMS > Coveo vs. Datomic vs. Google Cloud Firestore vs. InterSystems Caché vs. RocksDB

System Properties Comparison Coveo vs. Datomic vs. Google Cloud Firestore vs. InterSystems Caché vs. RocksDB

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

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A multi-model DBMS and application server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

Relational DBMS

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.coveo.com

www.datomic.com

firebase.google.com/products/firestore

www.intersystems.com/products/cache

rocksdb.org

Technical documentation

docs.coveo.com

docs.datomic.com

firebase.google.com/docs/firestore

docs.intersystems.com

github.com/facebook/rocksdb/wiki

Developer

Coveo

Cognitect

Google

InterSystems

Facebook, Inc.

Initial release

2012

2017

1997

2013

Current release

1.0.6735, June 2023

2018.1.4, May 2020

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD

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, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

hosted

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

Linux

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

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

APIs and other access methods

RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C#
Java
JavaScript
Python

Clojure
Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

By using transaction functions

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

But extensive use of caching in the application peers

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

granular access controls, API key management, content filters

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users, groups and roles

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