DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. DuckDB vs. LeanXcale vs. Spark SQL

System Properties Comparison Apache Impala vs. DuckDB vs. LeanXcale vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDuckDB  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, in-process, column-oriented SQL OLAP RDBMSA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgduckdb.orgwww.leanxcale.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlduckdb.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaLeanXcaleApache Software Foundation
Initial release2013201820152014
Current release4.1.0, June 20220.10, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Scala
Server operating systemsLinuxserver-lessLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infothrough Apache DerbySQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
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
C
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnono

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaDuckDBLeanXcaleSpark SQL
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Feature Engineering for Time-Series Using PySpark on Databricks
8 May 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Present your product here