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DBMS > Amazon DocumentDB vs. etcd vs. Oracle Berkeley DB vs. Spark SQL vs. TigerGraph

System Properties Comparison Amazon DocumentDB vs. etcd vs. Oracle Berkeley DB vs. Spark SQL vs. TigerGraph

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonetcd  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed reliable key-value storeWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeKey-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSGraph 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
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­documentdbetcd.io
github.com/­etcd-io/­etcd
www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.tigergraph.com
Technical documentationaws.amazon.com/­documentdb/­resourcesetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release2019199420142017
Current release3.4, August 201918.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infocommercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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 infoonly with the Berkeley DB XML editionnono
Secondary indexesyesnoyesno
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC
JSON over HTTP
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnonononoyes
Triggersnoyes, watching key changesyes infoonly for the SQL APInono
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 replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnono
User concepts infoAccess controlAccess rights for users and rolesnononoRole-based access control

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More resources
Amazon DocumentDBetcdOracle Berkeley DBSpark SQLTigerGraph
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