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DBMS > Apache Impala vs. Databricks vs. Kyligence Enterprise vs. QuestDB

System Properties Comparison Apache Impala vs. Databricks vs. Kyligence Enterprise vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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 distributed analytics engine for big data, built on top of Apache KylinA high performance open source SQL database for time series data
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websiteimpala.apache.orgwww.databricks.comkyligence.io/­kyligence-enterprisequestdb.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comquestdb.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksKyligence, Inc.QuestDB Technology Inc
Initial release2013201320162014
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava (Zero-GC), C++, Rust
Server operating systemsLinuxhostedLinuxLinux
macOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes infoschema-free via InfluxDB Line Protocol
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLANSI SQL for queries (using Apache Calcite)SQL with time-series extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID for single-table writes
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.nononoyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos
More information provided by the system vendor
Apache ImpalaDatabricksKyligence EnterpriseQuestDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
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