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DBMS > 4D vs. BigObject vs. HyperSQL vs. Vertica

System Properties Comparison 4D vs. BigObject vs. HyperSQL vs. Vertica

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonBigObject  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAnalytic DBMS for real-time computations and queriesMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBCloud 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 modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.4d.combigobject.iohsqldb.orgwww.vertica.com
Technical documentationdeveloper.4d.comdocs.bigobject.iohsqldb.org/­web/­hsqlDocsFrame.htmlvertica.com/­documentation
Developer4D, IncBigObject, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release1984201520012005
Current releasev20, April 20232.7.2, June 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infobased on BSD licensecommercial 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 languageJavaC++
Server operating systemsOS X
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
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 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 indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
fluentd
ODBC
RESTful HTTP API
HTTP API infoJDBC via HTTP
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages4D proprietary IDE
PHP
All languages supporting JDBC/ODBC
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesLuaJava, SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenonenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnonenoneMulti-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.noyesyesno
User concepts infoAccess controlUsers and groupsnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
4D infoformer name: 4th DimensionBigObjectHyperSQL infoalso known as HSQLDBVertica 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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4D infoformer name: 4th DimensionBigObjectHyperSQL infoalso known as HSQLDBVertica infoOpenText™ Vertica™
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