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

DBMS > Apache Impala vs. Citus vs. Databricks vs. InfinityDB

System Properties Comparison Apache Impala vs. Citus vs. Databricks vs. InfinityDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonInfinityDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A Java embedded Key-Value Store which extends the Java Map interface
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Key-value store
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Websiteimpala.apache.orgwww.citusdata.comwww.databricks.comboilerbay.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comdocs.databricks.comboilerbay.com/­infinitydb/­manual
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksBoiler Bay Inc.
Initial release2013201020132002
Current release4.1.0, June 20228.1, December 20184.0
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CJava
Server operating systemsLinuxLinuxhostedAll OS with a Java VM
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arrays
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.noyes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capability
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionswith Databricks SQLno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsyesnone
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 ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capability
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loads
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardno
More information provided by the system vendor
Apache ImpalaCitusDatabricksInfinityDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

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 ImpalaCitusDatabricksInfinityDB
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the 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

Ubicloud wants to build an open source alternative to AWS
5 March 2024, TechCrunch

Ubicloud reels in $16M for its open-source cloud platform
5 March 2024, SiliconANGLE News

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL ...
24 January 2019, blogs.microsoft.com

Microsoft Benchmarks Distributed PostgreSQL DBs
10 July 2023, Datanami

Distributed PostgreSQL Benchmarks: Azure Cosmos DB, CockroachDB, and YugabyteDB
8 July 2023, InfoQ.com

provided by Google News

Databricks is expanding the scope of its AI investments with second VC fund
21 May 2024, Fortune

Building CI Pipeline with Databricks Asset Bundle and GitLab
25 May 2024, hackernoon.com

XponentL Data Secures Strategic Investment from Databricks Ventures to Fuel Data Transformation & Generative AI
22 May 2024, Business Wire

XponentL Data Receives Strategic Investment from Databricks Ventures and Inoca Capital Partners
22 May 2024, FinSMEs

Analytics and Data Science News for the Week of May 24; Updates from Databricks, IBM, Microsoft & More
23 May 2024, Solutions Review

provided by Google News



Share this page

Featured Products

Neo4j logo

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

Milvus logo

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

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

RaimaDB logo

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

Present your product here