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DBMS > etcd vs. LeanXcale vs. Spark SQL vs. Tigris

System Properties Comparison etcd vs. LeanXcale vs. Spark SQL vs. Tigris

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionA distributed reliable key-value storeA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processingA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSDocument store
Key-value store
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.leanxcale.comspark.apache.org/­sqlwww.tigrisdata.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tigrisdata.com/­docs
DeveloperLeanXcaleApache Software FoundationTigris Data, Inc.
Initial release201520142022
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 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 languageGoScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesyes
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 indexesnonoyes
SQL infoSupport of SQLnoyes infothrough Apache DerbySQL-like DML and DDL statementsno
APIs and other access methodsgRPC
JSON over HTTP
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
CLI Client
gRPC
RESTful HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
Java
Scala
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresnonono
Triggersyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnonoAccess rights for users and roles

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More resources
etcdLeanXcaleSpark SQLTigris
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