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DBMS > Apache Phoenix vs. GigaSpaces vs. Hawkular Metrics vs. Postgres-XL vs. Vertica

System Properties Comparison Apache Phoenix vs. GigaSpaces vs. Hawkular Metrics vs. Postgres-XL vs. Vertica

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPostgres-XL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresCloud 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 DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
Spatial 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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitephoenix.apache.orgwww.gigaspaces.comwww.hawkular.orgwww.postgres-xl.orgwww.vertica.com
Technical documentationphoenix.apache.orgdocs.gigaspaces.com/­latest/­landing.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgres-xl.org/­documentationvertica.com/­documentation
DeveloperApache Software FoundationGigaspaces TechnologiesCommunity supported by Red HatOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014200020142014 infosince 2012, originally named StormDB2005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201915.5, September 202010 R1, October 201812.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0Open Source infoMozilla public licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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 languageJavaJava, C++, .NetJavaCC++
Server operating systemsLinux
Unix
Windows
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyesYes, 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 dateyesyesyesyesyes
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 infoXML can be used for describing objects metadatanoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-99 for query and DML statementsnoyes infodistributed, parallel query executionFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.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++
Java
Python
Scala
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsyesnouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, event driven architectureyes infovia Hawkular Alertingyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandrahorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
selectable replication factor infobased on 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 methodsHadoop integrationyes infoMap-Reduce pattern can be built with XAP task executorsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-based access controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PhoenixGigaSpacesHawkular MetricsPostgres-XLVertica 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 PhoenixGigaSpacesHawkular MetricsPostgres-XLVertica infoOpenText™ Vertica™
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