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DBMS > EventStoreDB vs. Hyprcubd vs. MarkLogic vs. Spark SQL

System Properties Comparison EventStoreDB vs. Hyprcubd vs. MarkLogic vs. Spark SQL

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Serverless Time Series DBMSOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelEvent StoreTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#173  Overall
#1  Event Stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.eventstore.comhyprcubd.com (offline)www.progress.com/­marklogicspark.apache.org/­sql
Technical documentationdevelopers.eventstore.comwww.progress.com/­marklogic/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEvent Store LimitedHyprcubd, Inc.MarkLogic Corp.Apache Software Foundation
Initial release201220012014
Current release21.2, February 202111.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
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 languageGoC++Scala
Server operating systemsLinux
Windows
hostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesyes
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.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLSQL-like query languageyes infoSQL92SQL-like DML and DDL statements
APIs and other access methodsgRPC (https)Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datanoyesyes
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, with Range Indexesno
User concepts infoAccess controltoken accessRole-based access control at the document and subdocument levelsno

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More resources
EventStoreDBHyprcubdMarkLogicSpark SQL
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