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DBMS > Google Cloud Bigtable vs. KeyDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. KeyDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. XTDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value store
Wide column store
Key-value storeRelational DBMS infocolumn orientedRelational DBMSDocument store
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitecloud.google.com/­bigtablegithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­services/­data-explorerwww.sadasengine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.keydb.devdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.xtdb.com/­docs
DeveloperGoogleEQ Alpha Technology Ltd.MicrosoftSADAS s.r.l.Juxt Ltd.
Initial release20152019201920062019
Current releasecloud service with continuous releases8.01.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3commercialcommercial infofree trial version availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Clojure
Server operating systemshostedLinuxhostedAIX
Linux
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or datenopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes, extensible-data-notation format
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.nonoyesnono
Secondary indexesnoyes infoby using the Redis Search moduleall fields are automatically indexedyesyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetyeslimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol infoRESP - REdis Serialization ProtocoMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
HTTP REST
JDBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresnoLuaYes, possible languages: KQL, Python, Rnono
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Strong eventual consistency with CRDTs
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsOptimistic locking, atomic execution of commands blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableKeyDBMicrosoft Azure Data ExplorerSadas EngineXTDB infoformerly named Crux
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