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DBMS > EsgynDB vs. Hawkular Metrics vs. Teradata vs. Vertica

System Properties Comparison EsgynDB vs. Hawkular Metrics vs. Teradata vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTeradata  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A hybrid cloud data analytics software platform (Teradata Vantage)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 modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cnwww.hawkular.orgwww.teradata.comwww.vertica.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.teradata.comvertica.com/­documentation
DeveloperEsgynCommunity supported by Red HatTeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201419842005
Current releaseTeradata Vantage 1.0 MU2, January 201912.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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 languageC++, JavaJavaC++
Server operating systemsLinuxLinux
OS X
Windows
hosted
Linux
Linux
Data schemeyesschema-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 dateyesyesyesyes
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.nonoyesno
Secondary indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoyes infoSQL 2016 + extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP REST.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGo
Java
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infoUDFs, stored procedures, table functions in parallelyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infovia Hawkular Alertingyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoHashinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
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 methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine 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
EsgynDBHawkular MetricsTeradataVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
EsgynDBHawkular MetricsTeradataVertica infoOpenText™ Vertica™
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