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DBMS > Sadas Engine vs. Trafodion vs. Vertica

System Properties Comparison Sadas Engine vs. Trafodion vs. Vertica

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Editorial information provided by DB-Engines
NameSadas Engine  Xexclude from comparisonTrafodion  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsTransactional SQL-on-Hadoop DBMSColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.01
Rank#347  Overall
#145  Relational DBMS
Score0.46
Rank#243  Overall
#116  Relational DBMS
Score20.33
Rank#35  Overall
#21  Relational DBMS
Websitewww.sadasengine.comtrafodion.apache.orgwww.vertica.com
Technical documentationwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbtrafodion.apache.orgwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperSADAS s.r.l.Apache Software Foundation, originally developed by HPVertica / Micro Focus infoprior to that Hewlett Packard
Initial release200620142005
Current release8.02.3.0, February 2019Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java
Server operating systemsAIX
Linux
Windows
LinuxLinux
Data schemeyesyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLyesyesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Groovy
Java
PHP
Python
All languages supporting JDBC/ODBC/ADO.NetC++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, via HBaseMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBaseyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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 infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardfine 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
Sadas EngineTrafodionVertica 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
Sadas EngineTrafodionVertica infoVertica Analytics Platform
Recent citations in the news

Apache Trafodion becomes Top-Level Project
10 January 2018, SDTimes.com

The ApacheĀ® Software Foundation Announces Annual Report for
31 August 2021, GlobeNewswire

provided by Google News

Vertica to Leverage NetApp StorageGRID to Deliver Cloud-Scale Analytics to On-Premises Environments
10 November 2021, PRNewswire

EDB unleashes BigAnimal in the cloud
2 November 2021, ZDNet

Vertica Announces Vertica 11, Delivering on Vision of Unified Analytics
20 July 2021, PRNewswire

Vertica Accelerator is Now Available on AWS
28 September 2021, Database Trends and Applications

Vertica Announces Early Access of Vertica Eon Accelerator and Acquisition of Full360
16 June 2021, Database Trends and Applications

provided by Google News

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