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DBMS > EsgynDB vs. Hive vs. Sphinx vs. Vertica

System Properties Comparison EsgynDB vs. Hive vs. Sphinx vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHive  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata warehouse software for querying and managing large distributed datasets, built on HadoopOpen source search engine for searching in data from different sources, e.g. relational databasesCloud 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 DBMSRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.esgyn.cnhive.apache.orgsphinxsearch.comwww.vertica.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homesphinxsearch.com/­docsvertica.com/­documentation
DeveloperEsgynApache Software Foundation infoinitially developed by FacebookSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201220012005
Current release3.1.3, April 20223.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availablecommercial 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++C++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesYes, 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.nono
Secondary indexesyesyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Proprietary protocolADO.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.NetC++
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reducenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factornoneMulti-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 methodsyesyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx 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 controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBHiveSphinxVertica 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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EsgynDBHiveSphinxVertica infoOpenText™ Vertica™
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