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DBMS > Elasticsearch vs. Google Cloud Datastore vs. RDF4J vs. Teradata Aster

System Properties Comparison Elasticsearch vs. Google Cloud Datastore vs. RDF4J vs. Teradata Aster

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA 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 metricAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Platform for big data analytics on multistructured data sources and types
Primary database modelSearch engineDocument storeRDF storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score132.83
Rank#7  Overall
#1  Search engines
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.elastic.co/­elasticsearchcloud.google.com/­datastorerdf4j.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperElasticGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release2010200820042005
Current release8.6, January 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Unix
Windows
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes infoRDF SchemasFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)noyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesusing Google App EngineyesR packages
Triggersyes infoby using the 'percolation' featureCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
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, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
ElasticsearchGoogle Cloud DatastoreRDF4J infoformerly known as SesameTeradata Aster
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