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

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

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA distributed reliable key-value storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully 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 storeKey-value store
Wide column store
Relational 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column 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
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerwww.sadasengine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.xtdb.com/­docs
DeveloperGoogleMicrosoftSADAS s.r.l.Juxt Ltd.
Initial release2015201920062019
Current release3.4, August 2019cloud service with continuous releases8.01.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree trial version availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Clojure
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedhostedAIX
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 datenonoyes 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 indexesnonoall fields are automatically indexedyesyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetyeslimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
HTTP REST
JDBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnono
Triggersyes, watching key changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zonesyes 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 methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, 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.nononoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdGoogle Cloud BigtableMicrosoft Azure Data ExplorerSadas EngineXTDB infoformerly named Crux
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