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DBMS > Databricks vs. etcd vs. Sadas Engine vs. Spark SQL vs. TypeDB

System Properties Comparison Databricks vs. etcd vs. Sadas Engine vs. Spark SQL vs. TypeDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonTypeDB infoformerly named Grakn  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 reliable key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSRelational DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
www.sadasengine.comspark.apache.org/­sqltypedb.com
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypedb.com/­docs
DeveloperDatabricksSADAS s.r.l.Apache Software FoundationVaticle
Initial release2013200620142016
Current release3.4, August 20198.03.5.0 ( 2.13), September 20232.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoApache 2.0Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++ScalaJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
AIX
Linux
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.yesnononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnononono
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark CoreSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenoneMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.nonoyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardnoyes infoat REST API level; other APIs in progress
More information provided by the system vendor
DatabricksetcdSadas EngineSpark SQLTypeDB infoformerly named Grakn
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
DatabricksetcdSadas EngineSpark SQLTypeDB infoformerly named Grakn
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