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DBMS > Amazon CloudSearch vs. HugeGraph vs. TigerGraph vs. Vertica

System Properties Comparison Amazon CloudSearch vs. HugeGraph vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonHugeGraph  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudA fast-speed and highly-scalable Graph DBMSA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud 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 modelSearch engineGraph DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteaws.amazon.com/­cloudsearchgithub.com/­hugegraph
hugegraph.apache.org
www.tigergraph.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­cloudsearchhugegraph.apache.org/­docsdocs.tigergraph.comvertica.com/­documentation
DeveloperAmazonBaiduOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201820172005
Current release0.912.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemshostedLinux
macOS
Unix
LinuxLinux
Data schemeyesyesyesYes, 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 dateyesyesyesyes
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.nonono
Secondary indexesyes infoall search fields are automatically indexedyes infoalso supports composite index and range indexNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGroovy
Java
Python
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-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 methodsnovia hugegraph-sparkyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlauthentication via encrypted signaturesUsers, roles and permissionsRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon CloudSearchHugeGraphTigerGraphVertica 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...
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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
Amazon CloudSearchHugeGraphTigerGraphVertica infoOpenText™ Vertica™
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