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DBMS > Amazon Neptune vs. Apache Impala vs. BoltDB vs. CouchDB vs. Google Cloud Bigtable

System Properties Comparison Amazon Neptune vs. Apache Impala vs. BoltDB vs. CouchDB vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Impala  Xexclude from comparisonBoltDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for HadoopAn embedded key-value store for Go.A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeDocument storeKey-value store
Wide column store
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.80
Rank#215  Overall
#31  Key-value stores
Score8.30
Rank#47  Overall
#7  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­neptuneimpala.apache.orggithub.com/­boltdb/­boltcouchdb.apache.orgcloud.google.com/­bigtable
Technical documentationaws.amazon.com/­neptune/­developer-resourcesimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stablecloud.google.com/­bigtable/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogle
Initial release20172013201320052015
Current release4.1.0, June 20223.3.3, December 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoErlang
Server operating systemshostedLinuxBSD
Linux
OS X
Solaris
Windows
Android
BSD
Linux
OS X
Solaris
Windows
hosted
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnonono
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.nonononono
Secondary indexesnoyesnoyes infovia viewsno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnonono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP/JSON APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCGoC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoView functions in JavaScriptno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infoimproved architecture with release 2.0Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable replication factornoneMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencynoneEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesno infoatomic operations within a single document possibleAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infostrategy: optimistic lockingyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon NeptuneApache ImpalaBoltDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud Bigtable
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