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DBMS > Databricks vs. etcd vs. Newts vs. Quasardb vs. Spark SQL

System Properties Comparison Databricks vs. etcd vs. Newts vs. Quasardb vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonNewts  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  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 storeTime Series DBMS based on CassandraDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Key-value storeTime Series DBMSTime Series DBMSRelational DBMS
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
#41  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
opennms.github.io/­newtsquasar.aispark.apache.org/­sql
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
github.com/­OpenNMS/­newts/­wikidoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksOpenNMS GroupquasardbApache Software Foundation
Initial release2013201420092014
Current release3.4, August 20193.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++Scala
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes infointeger and binaryyes
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 indexesyesnonoyes infowith tagsno
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
HTTP REST
Java API
HTTP APIJDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnononono
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factor infobased on CassandraSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infoTransient modeno
User concepts infoAccess controlnonoCryptographically strong user authentication and audit trailno
More information provided by the system vendor
DatabricksetcdNewtsQuasardbSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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