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DBMS > Blueflood vs. etcd vs. Kinetica vs. Spark SQL

System Properties Comparison Blueflood vs. etcd vs. Kinetica vs. Spark SQL

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonetcd  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraA distributed reliable key-value storeFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteblueflood.ioetcd.io
github.com/­etcd-io/­etcd
www.kinetica.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikietcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceKineticaApache Software Foundation
Initial release201320122014
Current release3.4, August 20197.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC, C++Scala
Server operating systemsLinux
OS X
FreeBSD
Linux
Windows infoexperimental
LinuxLinux
OS X
Windows
Data schemepredefined schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesnonoyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTgRPC
JSON over HTTP
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnoyes, watching key changesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnonoAccess rights for users and roles on table levelno

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More resources
BluefloodetcdKineticaSpark SQL
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