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DBMS > Kyligence Enterprise vs. Newts vs. PouchDB vs. Vertica

System Properties Comparison Kyligence Enterprise vs. Newts vs. PouchDB vs. Vertica

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Editorial information provided by DB-Engines
NameKyligence Enterprise  Xexclude from comparisonNewts  Xexclude from comparisonPouchDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA distributed analytics engine for big data, built on top of Apache KylinTime Series DBMS based on CassandraJavaScript DBMS with an API inspired by CouchDBCloud 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 DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitekyligence.io/­kyligence-enterpriseopennms.github.io/­newtspouchdb.comwww.vertica.com
Technical documentationgithub.com/­OpenNMS/­newts/­wikipouchdb.com/­guidesvertica.com/­documentation
DeveloperKyligence, Inc.OpenNMS GroupApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2016201420122005
Current release7.1.1, June 201912.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Sourcecommercial 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 languageJavaJavaJavaScriptC++
Server operating systemsLinuxLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeyesschema-freeschema-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 dateyesyesnoyes
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.nononono
Secondary indexesyesnoyes infovia viewsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP REST
Java API
HTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaJavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoView functions in JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
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 methodsyesnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Kyligence EnterpriseNewtsPouchDBVertica 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
Kyligence EnterpriseNewtsPouchDBVertica infoOpenText™ Vertica™
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