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DBMS > atoti vs. etcd vs. Sadas Engine vs. Spark SQL

System Properties Comparison atoti vs. etcd vs. Sadas Engine vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonetcd  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.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 processing
Primary database modelObject oriented DBMSKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented 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
Websiteatoti.ioetcd.io
github.com/­etcd-io/­etcd
www.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.atoti.ioetcd.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.html
DeveloperActiveViamSADAS s.r.l.Apache Software Foundation
Initial release20062014
Current release3.4, August 20198.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)noyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languages.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
Server-side scripts infoStored proceduresPythonnonono
Triggersyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioninghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
atotietcdSadas EngineSpark SQL
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