DBMS > Couchbase vs. GigaSpaces vs. Google Cloud Firestore vs. VelocityDB

System Properties Comparison Couchbase vs. GigaSpaces vs. Google Cloud Firestore vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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 .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Document store

Graph DBMS
Object oriented DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Search engine

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

www.couchbase.com

www.gigaspaces.com

firebase.google.com/products/firestore

velocitydb.com

Technical documentation

docs.couchbase.com

docs.gigaspaces.com/latest/landing.html

firebase.google.com/docs/firestore

velocitydb.com/UserGuide

Developer

Couchbase, Inc.

Gigaspaces Technologies

Google

VelocityDB Inc

Initial release

2011

2000

2017

2011

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

15.5, September 2020

7.x

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; Commercial licenses available

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.

Implementation language

C, C++, Go and Erlang

Java, C++, .Net

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

hosted

Any that supports .NET

Data scheme

schema-free

yes

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-99 for query and DML statements

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

.Net

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C++
Java
Python
Scala

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

.Net

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

yes, Firebase Rules & Cloud Functions

Triggers

yes

via the TAP protocol

yes, event driven architecture

yes, with Cloud Functions

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Role-based access control

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

Based on Windows Authentication

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