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DBMS > Datastax Enterprise vs. Vertica

System Properties Comparison Datastax Enterprise vs. Vertica

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Columnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelWide column storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.80
Rank#43  Overall
#4  Wide column stores
Score23.80
Rank#29  Overall
#17  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisewww.vertica.com
Technical documentationdocs.datastax.comwww.vertica.com/­documentation/­vertica
DeveloperDataStaxVertica / Micro Focus infoprior to that Hewlett Packard
Initial release20112005
Current release6.7, December 2018Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open Sourcecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenono 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 languageJava
Server operating systemsLinux
OS X
Linux
Data schemeschema-freeyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyes
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.noyes
Secondary indexesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Kafka
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyes
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users can be defined per objectfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Datastax EnterpriseVertica infoVertica Analytics Platform
Specific characteristics100% continuous availability, real-time, distributed, massive scale data management...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesSupporting the following application requirements: Contextual: complete data layer...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosApplications that must serve contextual information and be always-on, distributed,...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald’s, Microsoft, Safeway, Sony, UBS, and...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more
Cost-based models and subscription-based models are available
» more

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More resources
Datastax EnterpriseVertica infoVertica Analytics Platform
Recent citations in the news

DataStax and VMware Expand Collaboration for Hybrid Cloud Solutions
6 August 2019, Yahoo Finance

The Journey to Hybrid Cloud with DataStax Enterprise
2 August 2019, Computerworld

DataStax Announces Platinum Sponsorship of ApacheCon
24 July 2019, Yahoo Finance

MobilePay Capitalizes on Modern Apps With DataStax
29 July 2019, Yahoo Finance

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7 August 2019, ComputerWeekly.com

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