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

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonScyllaDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Distributed Event Store optimized for Internet of Things use casesCassandra and DynamoDB compatible wide column store
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.75
Rank#68  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
DeveloperDatabricksFatCloudIBMScyllaDB
Initial release2013201220172015
Current release2.0ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availableOpen Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 systemshostedWindowsLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-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.yesnono
Secondary indexesyesyesnoyes infocluster global secondary indices
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL Serveryes infothrough the embedded Spark runtimeSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
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#
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 aggregatesyes infovia applicationsyesyes, Lua
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorActive-active shard replicationselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - 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 controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardAccess rights for users can be defined per object
More information provided by the system vendor
DatabricksFatDBIBM 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...
» 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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DatabricksFatDBIBM Db2 Event StoreScyllaDB
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