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DBMS > Databricks vs. GridGain vs. Neo4j vs. Sphinx

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonNeo4j  Xexclude from comparisonSphinx  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.GridGain is an in-memory computing platform, built on Apache IgniteScalable, 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 databases
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Graph DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.gridgain.comneo4j.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlneo4j.com/­docssphinxsearch.com/­docs
DeveloperDatabricksGridGain Systems, Inc.Neo4j, Inc.Sphinx Technologies Inc.
Initial release2013200720072001
Current releaseGridGain 8.5.15.19, April 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version3, commercial licenses availableOpen 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, C++, .NetJava, ScalaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyesyesno
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.yesyes
Secondary indexesyesyesyes infopluggable indexing subsystem, by default Apache Luceneyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Proprietary protocol
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
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
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yes infoUser defined Procedures and Functionsno
Triggersyes (cache interceptors and events)yes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j FabricSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.noyes
User concepts infoAccess controlSecurity Hooks for custom implementationsUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)no
More information provided by the system vendor
DatabricksGridGainNeo4jSphinx
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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