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DBMS > Databricks vs. Graph Engine vs. RavenDB vs. Vitess

System Properties Comparison Databricks vs. Graph Engine vs. RavenDB vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonRavenDB  Xexclude from comparisonVitess  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Graph DBMS
Key-value store
Document storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Document store
Spatial 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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score2.84
Rank#101  Overall
#18  Document stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.databricks.comwww.graphengine.ioravendb.netvitess.io
Technical documentationdocs.databricks.comwww.graphengine.io/­docs/­manualravendb.net/­docsvitess.io/­docs
DeveloperDatabricksMicrosoftHibernating RhinosThe Linux Foundation, PlanetScale
Initial release2013201020102013
Current release5.4, July 202215.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC#Go
Server operating systemshosted.NETLinux
macOS
Raspberry Pi
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.yesno
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (RQL)yes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
C#
C++
F#
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesyes infoproprietary syntax
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAuthorization levels configured per client per databaseUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksGraph Engine infoformer name: TrinityRavenDBVitess
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGraph Engine infoformer name: TrinityRavenDBVitess
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