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DBMS > Amazon DocumentDB vs. Apache Impala vs. Brytlyt vs. Drizzle vs. JaguarDB

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. Brytlyt vs. Drizzle vs. JaguarDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonDrizzle  Xexclude from comparisonJaguarDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Performant, highly scalable DBMS for AI and IoT applications
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSKey-value store
Vector DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websiteaws.amazon.com/­documentdbimpala.apache.orgbrytlyt.iowww.jaguardb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmldocs.brytlyt.iowww.jaguardb.com/­support.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytDrizzle project, originally started by Brian AkerDataJaguar, Inc.
Initial release20192013201620082015
Current release4.1.0, June 20225.0, August 20237.2.4, September 20123.3 July 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoGNU GPLOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDAC++C++ infothe server part. Clients available in other languages
Server operating systemshostedLinuxLinux
OS X
Windows
FreeBSD
Linux
OS X
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyes infowith proprietary extensionsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnono
Triggersnonoyesno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPrights management via user accounts

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More resources
Amazon DocumentDBApache ImpalaBrytlytDrizzleJaguarDB
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