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DBMS > Apache Impala vs. Databricks vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Apache Impala vs. Databricks vs. Microsoft Azure Table Storage vs. XTDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  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 Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score0.09
Rank#351  Overall
#47  Document stores
Websiteimpala.apache.orgwww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksMicrosoftJuxt Ltd.
Initial release2013201320122019
Current release4.1.0, June 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Clojure
Server operating systemsLinuxhostedhostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, extensible-data-notation format
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
Apache ImpalaDatabricksMicrosoft Azure Table StorageXTDB infoformerly named Crux
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksMicrosoft Azure Table StorageXTDB infoformerly named Crux
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