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DBMS > Apache Impala vs. BigchainDB vs. Elasticsearch vs. OrigoDB vs. Spark SQL

System Properties Comparison Apache Impala vs. BigchainDB vs. Elasticsearch vs. OrigoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigchainDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA 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 metricA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeSearch engineDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score134.78
Rank#7  Overall
#1  Search engines
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.bigchaindb.comwww.elastic.co/­elasticsearchorigodb.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticRobert Friberg et alApache Software Foundation
Initial release2013201620102009 infounder the name LiveDB2014
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 infoAGPL v3Open Source infoElastic LicenseOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++PythonJavaC#Scala
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesnoyesUser defined using .NET types and collectionsyes
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 .NETno
Secondary indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
CLI Client
RESTful HTTP API
Java API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesno
Triggersnoyes infoby using the 'percolation' featureyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factoryesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoES-Hadoop Connectorno
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, all
Foreign keys infoReferential integritynononodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesRole based authorizationno

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More resources
Apache ImpalaBigchainDBElasticsearchOrigoDBSpark SQL
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