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DBMS > Databricks vs. FatDB vs. Microsoft Azure Table Storage vs. TypeDB vs. Yaacomo

System Properties Comparison Databricks vs. FatDB vs. Microsoft Azure Table Storage vs. TypeDB vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines 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.A Wide Column Store for rapid development using massive semi-structured datasetsTypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeGraph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.70
Rank#230  Overall
#20  Graph DBMS
#8  Object oriented DBMS
#106  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tablestypedb.comyaacomo.com
Technical documentationdocs.databricks.comtypedb.com/­docs
DeveloperDatabricksFatCloudMicrosoftVaticleQ2WEB GmbH
Initial release20132012201220162009
Current release2.28.3, June 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL Version 3, commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java
Server operating systemshostedWindowshostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL Servernonoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIgRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
JDBC
ODBC
Supported programming languagesPython
R
Scala
C#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsnono
Triggersyes infovia applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenohorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replication via raftSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesyes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFatDBMicrosoft Azure Table StorageTypeDB infoformerly named GraknYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
DatabricksFatDBMicrosoft Azure Table StorageTypeDB infoformerly named GraknYaacomo
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