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DBMS > Hawkular Metrics vs. Manticore Search vs. Vertica

System Properties Comparison Hawkular Metrics vs. Manticore Search vs. Vertica

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonManticore Search  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Multi-storage database for search, including full-text search.Cloud 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 modelTime Series DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibrarySpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.hawkular.orgmanticoresearch.comwww.vertica.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemanual.manticoresearch.comvertica.com/­documentation
DeveloperCommunity supported by Red HatManticore SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420172005
Current release6.0, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2commercial 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 languageJavaC++C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Windows
Linux
Data schemeschema-freeFixed schemaYes, 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 dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.noCan index from XMLno
Secondary indexesnoyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP RESTBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia Hawkular Alertingnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSynchronous replication based on Galera libraryMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Hawkular MetricsManticore SearchVertica 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
Hawkular MetricsManticore SearchVertica infoOpenText™ Vertica™
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