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DBMS > 4D vs. Apache Phoenix vs. SurrealDB vs. Vertica

System Properties Comparison 4D vs. Apache Phoenix vs. SurrealDB vs. Vertica

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache Phoenix  Xexclude from comparisonSurrealDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA scale-out RDBMS with evolutionary schema built on Apache HBaseA fully ACID transactional, developer-friendly, multi-model DBMSCloud 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 DBMSDocument store
Graph 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
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.4d.comphoenix.apache.orgsurrealdb.comwww.vertica.com
Technical documentationdeveloper.4d.comphoenix.apache.orgsurrealdb.com/­docsvertica.com/­documentation
Developer4D, IncApache Software FoundationSurrealDB LtdOpenText infopreviously Micro Focus and Hewlett Packard
Initial release1984201420222005
Current releasev20, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 2019v1.5.0, May 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Sourcecommercial 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 languageJavaRustC++
Server operating systemsOS X
Windows
Linux
Unix
Windows
Linux
macOS
Windows
Linux
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeYes, 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.yesnono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoclose to SQL 92yesSQL-like query languageFull 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
JDBCGraphQL
RESTful HTTP API
WebSocket
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
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Deno
Go
JavaScript (Node.js)
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
Multi-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 methodsnoHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.noyesno
User concepts infoAccess controlUsers and groupsAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes, based on authentication and database rulesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
4D infoformer name: 4th DimensionApache PhoenixSurrealDBVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
4D infoformer name: 4th DimensionApache PhoenixSurrealDBVertica infoOpenText™ Vertica™
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