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DBMS > OpenEdge vs. Spark SQL vs. Vertica vs. YTsaurus

System Properties Comparison OpenEdge vs. Spark SQL vs. Vertica vs. YTsaurus

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Editorial information provided by DB-Engines
NameOpenEdge  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemSpark SQL is a component on top of 'Spark Core' for structured data processingCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.YTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoColumn orientedDocument store
Key-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.21
Rank#324  Overall
#45  Document stores
#48  Key-value stores
Websitewww.progress.com/­openedgespark.apache.org/­sqlwww.vertica.comytsaurus.tech
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentationytsaurus.tech/­docs/­en
DeveloperProgress Software CorporationApache Software FoundationOpenText infopreviously Micro Focus and Hewlett PackardYandex
Initial release1984201420052023
Current releaseOpenEdge 12.2, March 20203.5.0 ( 2.13), September 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoLimited community edition freeOpen Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++
Server operating systemsAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
LinuxUbuntu
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnonono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.YQL, an SQL-based language, is supported
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesProgress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infosince Version 11.4yes, utilizing Spark Corehorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlUsers and groupsnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAccess Control Lists
More information provided by the system vendor
OpenEdgeSpark SQLVertica infoOpenText™ Vertica™YTsaurus
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
OpenEdgeSpark SQLVertica infoOpenText™ Vertica™YTsaurus
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