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DBMS > Apache Impala vs. CouchDB vs. Faircom EDGE vs. Google Cloud Bigtable

System Properties Comparison Apache Impala vs. CouchDB vs. Faircom EDGE vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsGoogle'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 modelRelational DBMSDocument storeKey-value store
Relational DBMS
Key-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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score8.30
Rank#47  Overall
#7  Document stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websiteimpala.apache.orgcouchdb.apache.orgwww.faircom.com/­products/­faircom-edgecloud.google.com/­bigtable
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stabledocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­bigtable/­docs
DeveloperApache 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 developerFairCom CorporationGoogle
Initial release2013200519792015
Current release4.1.0, June 20223.3.3, December 2023V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2commercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangANSI C, C++
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
Android
Linux infoARM, x86
Raspbian
Windows
hosted
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesnoyes, ANSI Standard SQL Typesno
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.nonoyesno
Secondary indexesyesyes infovia viewsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceView functions in JavaScriptyes info.Net, JavaScript, C/C++no
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0File partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyes infoacross SQL and NoSQLyes
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Faircom EDGE infoformerly c-treeEDGEGoogle Cloud Bigtable
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