DBMS > Coveo vs. Google Cloud Firestore vs. Google Cloud Spanner vs. jBASE vs. Yaacomo

System Properties Comparison Coveo vs. Google Cloud Firestore vs. Google Cloud Spanner vs. jBASE vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and 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

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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A robust multi-value DBMS comprising development tools and middleware

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Website

www.coveo.com

firebase.google.com/products/firestore

cloud.google.com/spanner

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

yaacomo.com

Technical documentation

docs.coveo.com

firebase.google.com/docs/firestore

cloud.google.com/spanner/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Coveo

Google

Rocket Software (formerly Zumasys)

Q2WEB GmbH

Initial release

2012

2017

1991

2009

Current release

5.7

License

Commercial or Open Source

commercial

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.

Server operating systems

hosted

AIX
Linux
Windows

Android
Linux
Windows

Data scheme

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

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

Query statements complying to ANSI 2011

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

RESTful HTTP API

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Python

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

Go
Java
JavaScript (Node.js)
Python

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication with 3 replicas for regional instances.

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

yes

ACID

Strict serializable isolation

ACID

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

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 based on Google Cloud Identity and Access Management (IAM)

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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Related products and services

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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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