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DBMS > Apache Impala vs. Databricks vs. ScyllaDB vs. Sequoiadb

System Properties Comparison Apache Impala vs. Databricks vs. ScyllaDB vs. Sequoiadb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonScyllaDB  Xexclude from comparisonSequoiadb  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.Cassandra and DynamoDB compatible wide column storeNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeDocument store
Relational DBMS
Secondary database modelsDocument storeKey-value 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
Score4.08
Rank#76  Overall
#5  Wide column stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comwww.scylladb.comwww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.scylladb.comwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksScyllaDBSequoiadb Ltd.
Initial release2013201320152013
Current release4.1.0, June 2022ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC++C++C++
Server operating systemsLinuxhostedLinuxLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infooid, date, timestamp, binary, regex
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 indexesyesyesyes infocluster global secondary indicesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLSQL-like DML and DDL statements (CQL)SQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes, LuaJavaScript
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factor infoRepresentation of geographical distribution of servers is possibleSource-replica replication
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 ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infoAtomicity and isolation are supported for single operationsDocument is locked during a transaction
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.nonoyes infoin-memory tablesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per objectsimple password-based access control
More information provided by the system vendor
Apache ImpalaDatabricksScyllaDBSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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