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DBMS > Spark SQL vs. Stardog vs. Vertica

System Properties Comparison Spark SQL vs. Stardog vs. Vertica

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonStardog  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.62
Rank#34  Overall
#21  Relational DBMS
Score1.36
Rank#144  Overall
#11  Graph DBMS
#6  RDF stores
Score21.58
Rank#31  Overall
#18  Relational DBMS
Websitespark.apache.org/­sqlwww.stardog.comwww.vertica.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.stardog.com/­docswww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperApache Software FoundationStardog-UnionVertica / Micro Focus infoprior to that Hewlett Packard
Initial release201420102005
Current release3.0.0, June 20207.3.0, May 2020Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaJava
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Linux
Data schemeyesschema-free and OWL/RDFS-schema supportyes infoUnstructured data can be stored in specific Flex-Tables
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 possibleyes
Secondary indexesnoyes infosupports real-time indexing in full-text and geospatialno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesJava
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregates, HTTP Server extensions in Javayes
Triggersnoyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication in HA-ClusterMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes
User concepts infoAccess controlnoAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Spark SQLStardogVertica infoVertica Analytics Platform
Specific characteristicsStardog is an Enterprise Knowledge Graph platform, uniquely combining graph storage...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesStardog provides a full featureset to aid in data integration for your complex data....
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosStardog is frequently used for: Anti-money laundering & fraud monitoring Customer...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersBosch, Dow Jones, Elsevier, Ericsson, Morgan Stanley, NASA, NIH, Nokia, Salesforce,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsStardog's technology is based on ground-breaking research by our founders cited 10,000+...
» more
Licensing and pricing modelsA fully-featured 60-day Trial license is available for those testing Stardog; contact...
» more
Cost-based models and subscription-based models are available
» more

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More resources
Spark SQLStardogVertica infoVertica Analytics Platform
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