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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonObjectBox  Xexclude from comparisonScyllaDB  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.Extremely fast embedded database for small devices, IoT and MobileCassandra and DynamoDB compatible wide column store
Primary database modelRelational DBMSDocument store
Relational DBMS
Object oriented DBMSWide column store
Secondary database modelsDocument storeTime Series DBMSKey-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
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Websiteimpala.apache.orgwww.databricks.comobjectbox.iowww.scylladb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.objectbox.iodocs.scylladb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksObjectBox LimitedScyllaDB
Initial release2013201320172015
Current release4.1.0, June 2022ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache License 2.0Open Source infoOpen Source (AGPL), commercial license available
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 and C++C++
Server operating systemsLinuxhostedAndroid
iOS
Linux
macOS
Windows
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
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 indexesyesyesyesyes infocluster global secondary indices
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnoSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Proprietary native APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoyes, Lua
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesonline/offline synchronization between client and serverselectable replication factor infoRepresentation of geographical distribution of servers is possible
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 ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno infoAtomicity and isolation are supported for single operations
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 infoin-memory tables
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess rights for users can be defined per object
More information provided by the system vendor
Apache ImpalaDatabricksObjectBoxScyllaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
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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