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DBMS > Amazon Neptune vs. Elasticsearch vs. OpenEdge vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon Neptune vs. Elasticsearch vs. OpenEdge vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonElasticsearch  Xexclude from comparisonOpenEdge  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Search engineRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score135.35
Rank#7  Overall
#1  Search engines
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunewww.elastic.co/­elasticsearchwww.progress.com/­openedgespark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperAmazonElasticProgress Software CorporationApache Software FoundationSphinx Technologies Inc.
Initial release20172010198420142001
Current release8.6, January 2023OpenEdge 12.2, March 20203.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemshostedAll OS with a Java VMAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonoyesno
Secondary indexesnoyes infoAll search fields are automatically indexedyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageyes infoclose to SQL 92SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesyesnono
Triggersnoyes infoby using the 'percolation' featureyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infosince Version 11.4yes, utilizing Spark CoreSharding 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.yesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectornono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes 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.Memcached and Redis integrationnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users and groupsnono

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More resources
Amazon NeptuneElasticsearchOpenEdgeSpark SQLSphinx
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