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DBMS > Hive vs. Snowflake vs. Vertica

System Properties Comparison Hive vs. Snowflake vs. Vertica

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSnowflake  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopCloud-based data warehousing service for structured and semi-structured dataCloud 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 DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score75.52
Rank#17  Overall
#11  Relational DBMS
Score114.13
Rank#11  Overall
#8  Relational DBMS
Score15.43
Rank#42  Overall
#27  Relational DBMS
Websitehive.apache.orgwww.snowflake.comwww.vertica.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.snowflake.net/­manuals/­index.htmlvertica.com/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookSnowflake Computing Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220142005
Current release3.1.3, April 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesno 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 SaaS.
Implementation languageJavaC++
Server operating systemsAll OS with a Java VMhostedLinux
Data schemeyesyes infosupport of semi-structured data formats (JSON, XML, Avro)Yes, 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.yesno
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Thrift
CLI Client
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
PHP
Python
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnono infosimilar concept for controling cloud resourcesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingyeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-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 MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
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 rolesUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HiveSnowflakeVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
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...
» more

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More resources
HiveSnowflakeVertica infoVertica Analytics Platform
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