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DBMS > Elasticsearch vs. Splice Machine vs. Stardog

System Properties Comparison Elasticsearch vs. Splice Machine vs. Stardog

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparison
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 metricOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelSearch engineRelational DBMSGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.79
Rank#7  Overall
#1  Search engines
Score0.54
Rank#257  Overall
#118  Relational DBMS
Score2.03
Rank#136  Overall
#12  Graph DBMS
#6  RDF stores
Websitewww.elastic.co/­elasticsearchsplicemachine.comwww.stardog.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsplicemachine.com/­how-it-worksdocs.stardog.com
DeveloperElasticSplice MachineStardog-Union
Initial release201020142010
Current release8.6, January 20233.1, March 20217.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoAGPL 3.0, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes
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.nono infoImport/export of XML data possible
Secondary indexesyes infoAll search fields are automatically indexedyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query languageyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoJavauser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infoby using the 'percolation' featureyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorYes, via Full Spark Integrationno
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 ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
ElasticsearchSplice MachineStardog
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Recent citations in the news

Introducing Elasticsearch Vector Database to Azure OpenAI Service On Your Data (Preview)
26 March 2024, insider.govtech.com

ElasticSearch Goes Deep on OpenTelemetry with eBPF Donation
13 March 2024, The New Stack

Elastic Announces 2023 Elastic Excellence Awards Winners
27 March 2024, Business Wire

Cribl forges strategic alliance with Elasticsearch for enhanced observability and AI integration
17 November 2023, SiliconANGLE News

12K Misconfigured Elasticsearch Buckets Ravaged by Extortionists
29 November 2023, Dark Reading

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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

New Splice Machine RDBMS unites OLTP and OLAP
18 November 2015, CIO

provided by Google News



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