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DBMS > Apache Impala vs. Databricks vs. SQream DB vs. YugabyteDB

System Properties Comparison Apache Impala vs. Databricks vs. SQream DB vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonSQream DB  Xexclude from comparisonYugabyteDB  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 GPU-based, columnar RDBMS for big data analytics workloadsHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Wide column store
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
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score2.63
Rank#109  Overall
#53  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comsqream.comwww.yugabyte.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.sqream.comdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksSQream TechnologiesYugabyte Inc.
Initial release2013201320172017
Current release4.1.0, June 20222022.1.6, December 20222.19, September 2023
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.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC++C++, CUDA, Haskell, Java, ScalaC and C++
Server operating systemsLinuxhostedLinuxLinux
OS X
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesdepending on used data model
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes
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.noyesno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyesyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesuser defined functions in Pythonyes infosql, plpgsql, C
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal and vertical partitioningHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
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 ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
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 Kerberosyes
More information provided by the system vendor
Apache ImpalaDatabricksSQream DBYugabyteDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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More resources
Apache ImpalaDatabricksSQream DBYugabyteDB
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