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DBMS > Amazon DocumentDB vs. LeanXcale vs. Rockset

System Properties Comparison Amazon DocumentDB vs. LeanXcale vs. Rockset

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonLeanXcale  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument storeKey-value store
Relational DBMS
Document store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Score0.84
Rank#209  Overall
#35  Document stores
Websiteaws.amazon.com/­documentdbwww.leanxcale.comrockset.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.rockset.com
DeveloperLeanXcaleRockset
Initial release201920152019
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhosted
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesdynamic typing
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.nono infoingestion from XML files supported
Secondary indexesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infothrough Apache DerbyRead-only SQL queries, including JOINs
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
HTTP REST
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
Java
Scala
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno
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
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and organizations can be defined via Rockset console

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More resources
Amazon DocumentDBLeanXcaleRockset
Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

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