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DBMS > Apache Phoenix vs. Microsoft Azure Table Storage vs. Vertica

System Properties Comparison Apache Phoenix vs. Microsoft Azure Table Storage vs. Vertica

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Wide Column Store for rapid development using massive semi-structured datasetsCloud 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 DBMSWide column storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitephoenix.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.vertica.com
Technical documentationphoenix.apache.orgvertica.com/­documentation
DeveloperApache Software FoundationMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420122005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial 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

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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows
hostedLinux
Data schemeyes 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 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.nonono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCRESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.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 methodsHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PhoenixMicrosoft Azure Table StorageVertica 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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More resources
Apache PhoenixMicrosoft Azure Table StorageVertica infoOpenText™ Vertica™
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
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