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DBMS > AlaSQL vs. HugeGraph vs. Kinetica vs. Solr vs. Stardog

System Properties Comparison AlaSQL vs. HugeGraph vs. Kinetica vs. Solr vs. Stardog

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionJavaScript DBMS libraryA fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LuceneEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument store
Relational DBMS
Graph DBMSRelational DBMSSearch engineGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitealasql.orggithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comsolr.apache.orgwww.stardog.com
Technical documentationgithub.com/­AlaSQL/­alasqlhugegraph.apache.org/­docsdocs.kinetica.comsolr.apache.org/­resources.htmldocs.stardog.com
DeveloperAndrey Gershun & Mathias R. WulffBaiduKineticaApache Software FoundationStardog-Union
Initial release20142018201220062010
Current release0.97.1, August 20219.6.0, April 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2commercial 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 servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaC, C++JavaJava
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Unix
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or datenoyesyesyes infosupports customizable data types and automatic typingyes
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.nononoyesno infoImport/export of XML data possible
Secondary indexesnoyes infoalso supports composite index and range indexyesyes infoAll search fields are automatically indexedyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.noSQL-like DML and DDL statementsSolr Parallel SQL InterfaceYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJavaScript APIJava API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
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 languagesJavaScriptGroovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsuser defined functionsJava pluginsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesyes infoedges in graphyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlnoUsers, roles and permissionsAccess rights for users and roles on table levelyesAccess rights for users and roles

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More resources
AlaSQLHugeGraphKineticaSolrStardog
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