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DBMS > Amazon Neptune vs. Databricks vs. GridGain vs. Sphinx

System Properties Comparison Amazon Neptune vs. Databricks vs. GridGain vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudThe 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 IgniteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Key-value store
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunewww.databricks.comwww.gridgain.comsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperAmazonDatabricksGridGain Systems, Inc.Sphinx Technologies Inc.
Initial release2017201320072001
Current releaseGridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.noyesyes
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.yesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
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 persistentyes infowith encyption-at-restyesyesyes 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 controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Security Hooks for custom implementationsno
More information provided by the system vendor
Amazon NeptuneDatabricksGridGainSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon NeptuneDatabricksGridGainSphinx
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