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DBMS > Apache Impala vs. Geode vs. Google Cloud Datastore vs. PouchDB

System Properties Comparison Apache Impala vs. Geode vs. Google Cloud Datastore vs. PouchDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSKey-value storeDocument storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score2.34
Rank#112  Overall
#21  Document stores
Websiteimpala.apache.orggeode.apache.orgcloud.google.com/­datastorepouchdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlgeode.apache.org/­docscloud.google.com/­datastore/­docspouchdb.com/­guides
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleApache Software Foundation
Initial release2013200220082012
Current release4.1.0, June 20221.1, February 20177.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaScript
Server operating systemsLinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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.nononono
Secondary indexesyesnoyesyes infovia views
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (OQL)SQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsusing Google App EngineView functions in JavaScript
Triggersnoyes infoCache Event ListenersCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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Apache ImpalaGeodeGoogle Cloud DatastorePouchDB
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