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DBMS > Apache Impala vs. Elasticsearch vs. Google Cloud Datastore vs. OrigoDB

System Properties Comparison Apache Impala vs. Elasticsearch vs. Google Cloud Datastore vs. OrigoDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fully ACID in-memory object graph database
Primary database modelRelational DBMSSearch engineDocument storeDocument store
Object oriented DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score4.36
Rank#72  Overall
#12  Document stores
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchcloud.google.com/­datastoreorigodb.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­datastore/­docsorigodb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticGoogleRobert Friberg et al
Initial release2013201020082009 infounder the name LiveDB
Current release4.1.0, June 20228.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicensecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereUser defined using .NET types and collections
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 infocan be achieved using .NET
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesusing Google App Engineyes
Triggersnoyes infoby using the 'percolation' featureCallbacks using the Google Apps Engineyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectoryes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate 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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsdepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorization

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More resources
Apache ImpalaElasticsearchGoogle Cloud DatastoreOrigoDB
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