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DBMS > Amazon DocumentDB vs. BigObject vs. Datastax Enterprise vs. Sequoiadb

System Properties Comparison Amazon DocumentDB vs. BigObject vs. Datastax Enterprise vs. Sequoiadb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBigObject  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for real-time computations and queriesDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.NewSQL database with distributed OLTP and SQL
Primary database modelDocument storeRelational DBMS infoa hierachical model (tree) can be imposedWide column storeDocument store
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score5.93
Rank#56  Overall
#4  Wide column stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Websiteaws.amazon.com/­documentdbbigobject.iowww.datastax.com/­products/­datastax-enterprisewww.sequoiadb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.bigobject.iodocs.datastax.comwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperBigObject, Inc.DataStaxSequoiadb Ltd.
Initial release2019201520112013
Current release6.8, April 2020
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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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
OS X
Linux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infooid, date, timestamp, binary, regex
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 indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)fluentd
ODBC
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
proprietary protocol using JSON
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoLuanoJavaScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneconfigurable replication factor, datacenter aware, advanced replication for edge computingSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono infoAtomicity and isolation are supported for single operationsDocument is locked during a transaction
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 rolesnoAccess rights for users can be defined per objectsimple password-based access control
More information provided by the system vendor
Amazon DocumentDBBigObjectDatastax EnterpriseSequoiadb
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Amazon DocumentDBBigObjectDatastax EnterpriseSequoiadb
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