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DBMS > Apache Impala vs. Badger vs. DuckDB vs. Elasticsearch vs. Spark SQL

System Properties Comparison Apache Impala vs. Badger vs. DuckDB vs. Elasticsearch vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonDuckDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.An embeddable, in-process, column-oriented SQL OLAP RDBMSA 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 metricSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engineRelational 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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerduckdb.orgwww.elastic.co/­elasticsearchspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerduckdb.org/­docswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsElasticApache Software Foundation
Initial release20132017201820102014
Current release4.1.0, June 20220.10, February 20248.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoMIT LicenseOpen Source infoElastic LicenseOpen 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++GoC++JavaScala
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
server-lessAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonononono
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesno
Triggersnononoyes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesMemcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnonono

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More resources
Apache ImpalaBadgerDuckDBElasticsearchSpark SQL
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