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DBMS > EsgynDB vs. Riak KV vs. Vertica

System Properties Comparison EsgynDB vs. Riak KV vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonRiak KV  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionDistributed, fault tolerant key-value storeColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#264  Overall
#124  Relational DBMS
Score5.67
Rank#57  Overall
#9  Key-value stores
Score22.55
Rank#29  Overall
#17  Relational DBMS
Websiteesgyn.combasho.com/­products/­riak-kvwww.vertica.com
Technical documentationesgyn.com/­developerswww.vertica.com/­documentation/­vertica
DeveloperEsgynBasho TechnologiesVertica / Micro Focus infoprior to that Hewlett Packard
Initial release201520092005
Current release2.1.0, April 2015Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editioncommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoavailable on Amazon AWS and Microsoft Azure
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaErlang
Server operating systemsLinuxLinux
OS X
Linux
Data schemeyesschema-freeyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesnoyes
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.nonoyes
Secondary indexesyesrestrictedno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLyesnoyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP API
Native Erlang Interface
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresJavaScript and Erlangyes
Triggersnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"Sharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication between multi datacentersselectable replication factorMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBRiak KVVertica infoVertica Analytics Platform
Specific characteristicsCapabilities for Operational/Transactional Workloads Deep Integration with HBase...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesEsgynDB is ideally suited to supporting Hybrid Transactional and Analytical Processing...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosIdeally suited to scenarios where high speed continuous data ingestion is required...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersEsgynDB's customers are worldwide, with several in the Global Fortune 500, including...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsEsgynDB Enterprise Edition is the commercially supported version of Apache Trafodion...
» more
Cost-based models and subscription-based models are available
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
EsgynDBRiak KVVertica infoVertica Analytics Platform
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