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DBMS > Google Cloud Firestore vs. Neo4j vs. RocksDB vs. Sphinx

System Properties Comparison Google Cloud Firestore vs. Neo4j vs. RocksDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonNeo4j  Xexclude from comparisonRocksDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionCloud 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.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeGraph DBMSKey-value storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.97
Rank#47  Overall
#8  Document stores
Score44.36
Rank#23  Overall
#1  Graph DBMS
Score4.52
Rank#80  Overall
#10  Key-value stores
Score6.06
Rank#61  Overall
#6  Search engines
Websitefirebase.google.com/­products/­firestoreneo4j.comrocksdb.orgsphinxsearch.com
Technical documentationfirebase.google.com/­docs/­firestoreneo4j.com/­docsgithub.com/­facebook/­rocksdb/­wikisphinxsearch.com/­docs
DeveloperGoogleNeo4j, Inc.Facebook, Inc.Sphinx Technologies Inc.
Initial release2017200720132001
Current release5.18.1, March 20248.10.0, December 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoBSDOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaC++C++
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free and schema-optionalschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Lucenenoyes infofull-text index on all search fields
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
C++ API
Java API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C
C++
Go
Java
Perl
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoUser defined Procedures and Functionsnono
Triggersyes, with Cloud Functionsyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j Fabrichorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynoyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)nono
More information provided by the system vendor
Google Cloud FirestoreNeo4jRocksDBSphinx
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
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