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DBMS > Amazon DocumentDB vs. Firebolt vs. Memcached vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Firebolt vs. Memcached vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFirebolt  Xexclude from comparisonMemcached  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseIn-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.firebolt.iowww.memcached.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.firebolt.iogithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFirebolt Analytics Inc.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release2019202020032014
Current release1.6.27, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemshostedhostedFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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
Secondary indexesyesyesnono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).Net
ODBC
RESTful HTTP API
Proprietary protocolJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasdepending on storage layernone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesyes infousing SASL (Simple Authentication and Security Layer) protocolno

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Amazon DocumentDBFireboltMemcachedSpark SQL
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