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DBMS > 4D vs. LeanXcale vs. Vertica

System Properties Comparison 4D vs. LeanXcale vs. Vertica

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonLeanXcale  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesCloud or on-premises 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 DBMSKey-value store
Relational DBMS
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.83
Rank#106  Overall
#55  Relational DBMS
Score0.17
Rank#297  Overall
#43  Key-value stores
#138  Relational DBMS
Score19.04
Rank#38  Overall
#24  Relational DBMS
Websitewww.4d.comwww.leanxcale.comwww.vertica.com
Technical documentationlivedoc.4d.comvertica.com/­documentation
Developer4D, IncLeanXcaleMicro Focus infoprior to that Hewlett Packard
Initial release198420152005
Current releasev18 R5, January 202111.1, February 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageC++
Server operating systemsOS X
Windows
Linux
Data schemeyesyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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.yesno
Secondary indexesyesNo Indexes Required
SQL infoSupport of SQLyes infoclose to SQL 92yes infothrough Apache DerbyFull 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
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages4D proprietary IDE
PHP
C
Java
Scala
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.noyesno
User concepts infoAccess controlUsers and groupsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
4D infoformer name: 4th DimensionLeanXcaleVertica infoVertica Analytics Platform
Specific characteristicsFull ACID and full SQL operational database with analytical queries over operational...
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Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
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Competitive advantagesLinear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
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Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosHybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersbanking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics15 beta testers
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Licensing and pricing modelsannual fee covering license and support based on number of physical cores
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Cost-based models and subscription-based models are both available. One license is...
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4D infoformer name: 4th DimensionLeanXcaleVertica infoVertica Analytics Platform
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