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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonLeanXcale  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeKey-value store
Relational DBMS
Vector DBMSRelational 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
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.leanxcale.comwww.pinecone.iospark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperLeanXcalePinecone Systems, IncApache Software Foundation
Initial release201520192014
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoString, Number, Booleanyes
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 indexesnono
SQL infoSupport of SQLnoyes infothrough Apache DerbynoSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP APIJDBC
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
Scala
PythonJava
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesyes, 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.none
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 datanoACIDno
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.noyesnono
User concepts infoAccess controlnono

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More resources
etcdLeanXcalePineconeSpark SQL
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