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DBMS > Realm vs. Spark SQL vs. STSdb vs. Vertica

System Properties Comparison Realm vs. Spark SQL vs. STSdb vs. Vertica

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Editorial information provided by DB-Engines
NameRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud 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.
Primary database modelDocument storeRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.71
Rank#52  Overall
#9  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websiterealm.iospark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentation
DeveloperRealm, acquired by MongoDB in May 2019Apache Software FoundationSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201420112005
Current release3.5.0 ( 2.13), September 20234.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC#C++
Server operating systemsAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
WindowsLinux
Data schemeyesyesyesYes, 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 dateyesyesyes infoprimitive types and user defined types (classes)yes
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.nonono
Secondary indexesyesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresno inforuns within the applications so server-side scripts are unnecessarynonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoChange Listenersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yes infoIn-Memory realmnono
User concepts infoAccess controlyesnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
RealmSpark SQLSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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RealmSpark SQLSTSdbVertica infoOpenText™ Vertica™
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