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DBMS > Amazon DocumentDB vs. etcd vs. LeanXcale vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. etcd vs. LeanXcale vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonetcd  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed reliable key-value storeA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeKey-value storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbetcd.io
github.com/­etcd-io/­etcd
www.leanxcale.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperLeanXcaleApache Software Foundation
Initial release201920152014
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
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.
Implementation languageGoScala
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLnonoyes infothrough Apache DerbySQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC
JSON over HTTP
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnoyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesnoneyes, 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 replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.none
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlAccess rights for users and rolesnono

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More resources
Amazon DocumentDBetcdLeanXcaleSpark SQL
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