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DBMS > Amazon DocumentDB vs. BigObject vs. HugeGraph vs. Vertica

System Properties Comparison Amazon DocumentDB vs. BigObject vs. HugeGraph vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBigObject  Xexclude from comparisonHugeGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for real-time computations and queriesA fast-speed and highly-scalable Graph DBMSCloud 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 storeRelational DBMS infoa hierachical model (tree) can be imposedGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­documentdbbigobject.iogithub.com/­hugegraph
hugegraph.apache.org
www.vertica.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.bigobject.iohugegraph.apache.org/­docsvertica.com/­documentation
DeveloperBigObject, Inc.BaiduOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2019201520182005
Current release0.912.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2.0commercial 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++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
macOS
Unix
Linux
Data schemeschema-freeyesyesYes, 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.nononono
Secondary indexesyesyesyes infoalso supports composite index and range indexNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)fluentd
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Groovy
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoLuaasynchronous Gremlin script jobsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneyes 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)novia hugegraph-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoautomatically between fact table and dimension tablesyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesyesno
User concepts infoAccess controlAccess rights for users and rolesnoUsers, roles and permissionsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon DocumentDBBigObjectHugeGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Amazon DocumentDBBigObjectHugeGraphVertica infoOpenText™ Vertica™
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