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DBMS > Hypertable vs. OmniSci vs. Vertica

System Properties Comparison Hypertable vs. OmniSci vs. Vertica

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA high performance, in-memory, column-oriented RDBMS, designed to run on GPUsColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.08
Rank#105  Overall
#52  Relational DBMS
Score22.51
Rank#29  Overall
#17  Relational DBMS
Websitewww.omnisci.comwww.vertica.com
Technical documentationwww.omnisci.com/­docs/­latestwww.vertica.com/­documentation/­vertica
DeveloperHypertable Inc.MapD Technologies, Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release200920162005
Current release0.9.8.11, March 2016V4Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2; enterprise edition availablecommercial 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

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Implementation languageC++C++ and CUDA
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Data schemeschema-freeyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or datenoyesyes
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 indexesrestricted infoonly exact value or prefix value scansnono infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLnoyesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsC++ API
Thrift
Thrift
JDBC
ODBC
Kafka
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnonoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelMaster-master replicationMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HypertableOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Vertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» 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 available
» more

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More resources
HypertableOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Vertica infoVertica Analytics Platform
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