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DBMS > Apache Impala vs. Elasticsearch vs. Google Cloud Datastore vs. Spark SQL

System Properties Comparison Apache Impala vs. Elasticsearch vs. Google Cloud Datastore vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  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 PlatformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument storeRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score4.47
Rank#76  Overall
#12  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchcloud.google.com/­datastorespark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticGoogleApache Software Foundation
Initial release2013201020082014
Current release4.1.0, June 20228.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScala
Server operating systemsLinuxAll OS with a Java VMhostedLinux
OS X
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 hereyes
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 indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesusing Google App Engineno
Triggersnoyes infoby using the 'percolation' featureCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectoryes infousing Google Cloud Dataflow
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 pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noMemcached and Redis integrationnono
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)no

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More resources
Apache ImpalaElasticsearchGoogle Cloud DatastoreSpark SQL
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