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DBMS > Elasticsearch vs. NSDb vs. Vertica

System Properties Comparison Elasticsearch vs. NSDb vs. Vertica

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonNSDb  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesCloud or on-premises 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 modelSearch engineTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score157.69
Rank#8  Overall
#1  Search engines
Score0.00
Rank#354  Overall
#33  Time Series DBMS
Score19.29
Rank#38  Overall
#24  Relational DBMS
Websitewww.elastic.co/­elasticsearchnsdb.iowww.vertica.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlnsdb.io/­Architecturevertica.com/­documentation
DeveloperElasticMicro Focus infoprior to that Hewlett Packard
Initial release201020172005
Current release7.8.0, June 202011.1, February 2022
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2.0commercial 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

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageJavaJava, ScalaC++
Server operating systemsAll OS with a Java VMLinux
macOS
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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 indexesyes infoAll search fields are automatically indexedall fields are automatically indexedNo Indexes Required
SQL infoSupport of SQLSQL-like query languageSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJava API
RESTful HTTP/JSON API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Scala
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoby using the 'percolation' featureyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-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 methodsES-Hadoop Connectornono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual 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 persistentyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationno
User concepts infoAccess controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
ElasticsearchNSDbVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantagesFast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
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...
» more

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More resources
ElasticsearchNSDbVertica infoVertica Analytics Platform
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

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3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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