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DBMS > etcd vs. Google Cloud Firestore vs. InfinityDB vs. IRONdb vs. Microsoft Azure Data Explorer

System Properties Comparison etcd vs. Google Cloud Firestore vs. InfinityDB vs. IRONdb vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.A Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platform
Primary database modelKey-value storeDocument storeKey-value storeTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestoreboilerbay.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorer
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestoreboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGoogleBoiler Bay Inc.Circonus LLC.Microsoft
Initial release2017200220172019
Current release3.4, August 20194.0V0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC and C++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VMLinuxhosted
Data schemeschema-freeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilitynoall fields are automatically indexed
SQL infoSupport of SQLnononoSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subset
APIs and other access methodsgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
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
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsnoyes, in LuaYes, possible languages: KQL, Python, R
Triggersyes, watching key changesyes, with Cloud Functionsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud service
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 replicationnoneconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud DataflownonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infoOptimistic locking for transactions; no isolation for bulk loadsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
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.nonoAzure Active Directory Authentication

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More resources
etcdGoogle Cloud FirestoreInfinityDBIRONdbMicrosoft Azure Data Explorer
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