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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonElasticsearch  Xexclude from comparisonGigaSpaces  Xexclude from comparisonOpenEdge  Xexclude from comparisonSpark SQL  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 metricHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Search engineDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Graph 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
Score135.35
Rank#7  Overall
#1  Search engines
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.elastic.co/­elasticsearchwww.gigaspaces.comwww.progress.com/­openedgespark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.gigaspaces.com/­latest/­landing.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonElasticGigaspaces TechnologiesProgress Software CorporationApache Software Foundation
Initial release20172010200019842014
Current release8.6, January 202315.5, September 2020OpenEdge 12.2, March 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicenseOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache 2.0
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 languageJavaJava, C++, .NetScala
Server operating systemshostedAll OS with a Java VMLinux
macOS
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonono infoXML can be used for describing objects metadatayesno
Secondary indexesnoyes infoAll search fields are automatically indexedyesyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-99 for query and DML statementsyes infoclose to SQL 92SQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyesyesno
Triggersnoyes infoby using the 'percolation' featureyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning infosince Version 11.4yes, utilizing Spark Core
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.yesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryes infoMap-Reduce pattern can be built with XAP task executorsno
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 infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlUsers and groupsno

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More resources
Amazon NeptuneElasticsearchGigaSpacesOpenEdgeSpark SQL
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