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DBMS > etcd vs. Google Cloud Firestore vs. HarperDB vs. Kinetica vs. ReductStore

System Properties Comparison etcd vs. Google Cloud Firestore vs. HarperDB vs. Kinetica vs. ReductStore

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionA distributed reliable key-value storeCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUsDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelKey-value storeDocument storeDocument storeRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
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
Score7.85
Rank#51  Overall
#8  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorewww.harperdb.iowww.kinetica.comgithub.com/­reductstore
www.reduct.store
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestoredocs.harperdb.io/­docsdocs.kinetica.comwww.reduct.store/­docs
DeveloperGoogleHarperDBKineticaReductStore LLC
Initial release2017201720122023
Current release3.4, August 20193.1, August 20217.1, August 20211.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition availablecommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoNode.jsC, C++C++, Rust
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
LinuxDocker
Linux
macOS
Windows
Data schemeschema-freeschema-freedynamic schemayes
Typing infopredefined data types such as float or datenoyesyes infoJSON data typesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLnonoSQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1user defined functions
Triggersyes, watching key changesyes, with Cloud Functionsnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationyes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and rolesAccess rights for users and roles on table level

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More resources
etcdGoogle Cloud FirestoreHarperDBKineticaReductStore
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