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DBMS > MarkLogic vs. Sadas Engine vs. Vertica

System Properties Comparison MarkLogic vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.45
Rank#48  Overall
#8  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Score0.00
Rank#354  Overall
#143  Relational DBMS
Score21.10
Rank#35  Overall
#21  Relational DBMS
Websitewww.marklogic.comwww.sadasengine.comwww.vertica.com
Technical documentationdocs.marklogic.comwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperMarkLogic Corp.SADAS s.r.l.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release200120062005
Current release9.0, 20178.0Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercial infofree trial version availablecommercial 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++
Server operating systemsLinux
OS X
Windows
AIX
Linux
Windows
Linux
Data schemeschema-free infoSchema can be enforcedyesyes 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.yesnoyes
Secondary indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLyes infoSQL92yesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionACID
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, with Range Indexesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
MarkLogicSadas EngineVertica infoVertica Analytics Platform
Specific characteristicsThe MarkLogic Multi-Model Database provides the simplest way to integrate data from...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesThe main benefit of MarkLogic is simplicity. By making things simpler, MarkLogic...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosMarkLogic’s main use case is the Operational Data Hub . A Data Hub is useful for...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersMarkLogic has proven results managing mission-critical data with over 1,000 global...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsMarkLogic is well known within the Fortune 1000, with a strong presence in financial...
» more
Licensing and pricing modelsMarkLogic provides a variety of licenses and cloud services: MarkLogic Data Hub Service...
» more
Cost-based models and subscription-based models are available
» more

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More resources
MarkLogicSadas EngineVertica infoVertica Analytics Platform
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