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DBMS > BoltDB vs. Google Cloud Firestore vs. Hive vs. Neo4j

System Properties Comparison BoltDB vs. Google Cloud Firestore vs. Hive vs. Neo4j

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHive  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionAn embedded key-value store for Go.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.data warehouse software for querying and managing large distributed datasets, built on HadoopScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelKey-value storeDocument storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Websitegithub.com/­boltdb/­boltfirebase.google.com/­products/­firestorehive.apache.orgneo4j.com
Technical documentationfirebase.google.com/­docs/­firestorecwiki.apache.org/­confluence/­display/­Hive/­Homeneo4j.com/­docs
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookNeo4j, Inc.
Initial release2013201720122007
Current release3.1.3, April 20225.19, April 2024
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2Open Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageGoJavaJava, Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VMLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-free and schema-optional
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesyesyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languagesGoGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
PHP
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infouser defined functions and integration of map-reduceyes infoUser defined Procedures and Functions
Triggersnoyes, with Cloud Functionsnoyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationselectable replication factorCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoAccess 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 rolesUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
BoltDBGoogle Cloud FirestoreHiveNeo4j
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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