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DBMS > Firebird vs. Hive vs. Neo4j vs. Splice Machine

System Properties Comparison Firebird vs. Hive vs. Neo4j vs. Splice Machine

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Editorial information provided by DB-Engines
NameFirebird  Xexclude from comparisonHive  Xexclude from comparisonNeo4j  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFirebird is an open source RDBMS forked from Borland's InterBasedata 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 offeringsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.50
Rank#30  Overall
#18  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.firebirdsql.orghive.apache.orgneo4j.comsplicemachine.com
Technical documentationwww.firebirdsql.org/­en/­reference-manualscwiki.apache.org/­confluence/­display/­Hive/­Homeneo4j.com/­docssplicemachine.com/­how-it-works
DeveloperFirebird FoundationApache Software Foundation infoinitially developed by FacebookNeo4j, Inc.Splice Machine
Initial release2000 infoAs fork of Borland's InterBase201220072014
Current release5.0.0, January 20243.1.3, April 20225.20, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2Open Source infoGPL version3, commercial licenses availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
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 languageC and C++JavaJava, ScalaJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
All OS with a Java VMLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyesyesyesyes
Secondary indexesyesyesyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes
APIs and other access methodsADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Thrift
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresPSQLyes infouser defined functions and integration of map-reduceyes infoUser defined Procedures and Functionsyes infoJava
Triggersyesnoyes infovia event handleryes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes using Neo4j FabricShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes, multi-version concurrency control (MVCC)
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.yes
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and rolesUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
FirebirdHiveNeo4jSplice Machine
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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