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DBMS > Databricks vs. IBM Db2 Event Store vs. ScyllaDB

System Properties Comparison Databricks vs. IBM Db2 Event Store vs. ScyllaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonScyllaDB  Xexclude from comparison
DescriptionThe 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.Distributed Event Store optimized for Internet of Things use casesCassandra and DynamoDB compatible wide column store
Primary database modelDocument store
Relational DBMS
Event Store
Time Series DBMS
Wide column store
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score5.27
Rank#67  Overall
#5  Wide column stores
Websitewww.databricks.comwww.ibm.com/­products/­db2-event-storewww.scylladb.com
Technical documentationdocs.databricks.comwww.ibm.com/­docs/­en/­db2-event-storedocs.scylladb.com
DeveloperDatabricksIBMScyllaDB
Initial release201320172015
Current release2.0ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
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 and C++C++
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyesnoyes infocluster global secondary indices
SQL infoSupport of SQLwith Databricks SQLyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesPython
R
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
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 proceduresuser defined functions and aggregatesyesyes, Lua
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive-active shard replicationselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoin-memory tables
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per object
More information provided by the system vendor
DatabricksIBM Db2 Event StoreScyllaDB
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...
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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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DatabricksIBM Db2 Event StoreScyllaDB
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