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DBMS > Hive vs. TypeDB vs. Vertica

System Properties Comparison Hive vs. TypeDB vs. Vertica

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query languageCloud 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 DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitehive.apache.orgtypedb.comwww.vertica.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Hometypedb.com/­docsvertica.com/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookVaticleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220162005
Current release3.1.3, April 20222.26.3, January 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL Version 3, commercial licenses availablecommercial 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

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
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 dateyesyesyes
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.nono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Thrift
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
PHP
Python
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infoby using CassandraMulti-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 methodsyes infoquery execution via MapReduceyes infoby using Apache Kafka and Apache Zookeeperno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.nono
User concepts infoAccess controlAccess rights for users, groups and rolesyes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HiveTypeDB infoformerly named GraknVertica infoOpenText™ Vertica™
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
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Communication 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 modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
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Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
HiveTypeDB infoformerly named GraknVertica infoOpenText™ Vertica™
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