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DBMS > Databricks vs. Neo4j vs. Sphinx vs. STSdb

System Properties Comparison Databricks vs. Neo4j vs. Sphinx vs. STSdb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNeo4j  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen source search engine for searching in data from different sources, e.g. relational databasesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Relational DBMS
Graph DBMSSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score44.47
Rank#23  Overall
#1  Graph DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.06
Rank#365  Overall
#55  Key-value stores
Websitewww.databricks.comneo4j.comsphinxsearch.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.databricks.comneo4j.com/­docssphinxsearch.com/­docs
DeveloperDatabricksNeo4j, Inc.Sphinx Technologies Inc.STS Soft SC
Initial release2013200720012011
Current release5.18.1, March 20243.5.1, February 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license 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
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and schema-optionalyesyes
Typing infopredefined data types such as float or dateyesnoyes infoprimitive types and user defined types (classes)
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.yes
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Luceneyes infofull-text index on all search fieldsno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Proprietary protocol.NET Client API
Supported programming languagesPython
R
Scala
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoUser defined Procedures and Functionsnono
Triggersyes infovia event handlernono
Partitioning methods infoMethods for storing different data on different nodesyes using Neo4j FabricSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)nono
More information provided by the system vendor
DatabricksNeo4jSphinxSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Neo4j 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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