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DBMS > MarkLogic vs. Qdrant vs. Sphinx vs. Teradata Aster vs. Vertica

System Properties Comparison MarkLogic vs. Qdrant vs. Sphinx vs. Teradata Aster vs. Vertica

Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonQdrant  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOperational and transactional Enterprise NoSQL databaseA high-performance vector database with neural network or semantic-based matchingOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and typesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Vector DBMSSearch engineRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.marklogic.comgithub.com/­qdrant/­qdrant
qdrant.tech
sphinxsearch.comwww.vertica.com
Technical documentationdocs.marklogic.comqdrant.tech/­documentationsphinxsearch.com/­docsvertica.com/­documentation
DeveloperMarkLogic Corp.QdrantSphinx Technologies Inc.TeradataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20012021200120052005
Current release11.0, December 20223.5.1, February 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++RustC++C++
Server operating systemsLinux
OS X
Windows
Docker
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxLinux
Data schemeschema-free infoSchema can be enforcedschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File StoreYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleannoyesyes
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 infoin Aster File Storeno
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textyes infofull-text index on all search fieldsyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoSQL92noSQL-like query language (SphinxQL)yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
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
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoR packagesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesCollection-level replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnonoyes infoSQL Map-Reduce Frameworkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency, tunable consistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesnono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsKey-based authenticationnofine 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
MarkLogicQdrantSphinxTeradata AsterVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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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 both available. One license is...
» more

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More resources
MarkLogicQdrantSphinxTeradata AsterVertica infoOpenText™ Vertica™
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