DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Druid vs. Apache Impala vs. Bangdb vs. Spark SQL

System Properties Comparison Apache Druid vs. Apache Impala vs. Bangdb vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgimpala.apache.orgbangdb.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.bangdb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBApache Software Foundation
Initial release2012201320122014
Current release29.0.1, April 20244.1.0, June 2022BangDB 2.0, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoBSD 3Open 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 languageJavaC++C, C++Scala
Server operating systemsLinux
OS X
Unix
LinuxLinuxLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes: string, long, double, int, geospatial, stream, eventsyes
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 indexesyesyesyes infosecondary, composite, nested, reverse, geospatialno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL like support with command line toolSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Java
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenono
Triggersnonoyes, Notifications (with Streaming only)no
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyTunable consistency, set CAP knob accordingly
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, optimistic concurrency controlyes
Durability infoSupport for making data persistentyesyesyes, implements WAL (Write ahead log) as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, run db with in-memory only modeno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)no

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 DruidApache ImpalaBangdbSpark SQL
Recent citations in the news

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, Business Wire

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, 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

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 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

RaimaDB logo

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

Neo4j logo

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

AllegroGraph logo

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

Present your product here