DBMS > GigaSpaces vs. Google Cloud Firestore vs. HarperDB vs. RocksDB

System Properties Comparison GigaSpaces vs. Google Cloud Firestore vs. HarperDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store

Key-value store

Secondary database models

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Trend Chart

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.gigaspaces.com

firebase.google.com/products/firestore

www.harperdb.io

rocksdb.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

firebase.google.com/docs/firestore

docs.harperdb.io/docs

github.com/facebook/rocksdb/wiki

Developer

Gigaspaces Technologies

Google

HarperDB

Facebook, Inc.

Initial release

2000

2017

2013

Current release

15.5, September 2020

3.1, August 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

free community edition available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Node.js

C++

Server operating systems

Linux
macOS
Solaris
Windows

hosted

Linux
OS X

Linux

Data scheme

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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-99 for query and DML statements

SQL-like data manipulation statements

APIs and other access methods

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

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Java API

Supported programming languages

.Net
C++
Java
Python
Scala

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Custom Functions

since release 3.1

Triggers

yes, event driven architecture

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

yes

the nodes on which a table resides can be defined

yes

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

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

Atomic execution of specific operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

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.

Access rights for users and roles

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