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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparisonYugabyteDB  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.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 queriesHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelKey-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMSDocument storeRelational DBMS
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
Document store
Wide column store
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerwww.sadasengine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
www.yugabyte.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.xtdb.com/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperGoogleMicrosoftSADAS s.r.l.Juxt Ltd.Yugabyte Inc.
Initial release20152019200620192017
Current releasecloud service with continuous releases8.01.19, September 20212.19, September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC++ClojureC and C++
Server operating systemshostedhostedAIX
Linux
Windows
All OS with a Java 8 (and higher) VM
Linux
Linux
OS X
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-freedepending on used data model
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes, extensible-data-notation formatyes
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.noyesnonono
Secondary indexesnoall fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetyeslimited SQL, making use of Apache Calciteyes, PostgreSQL compatible
APIs and other access methodsgRPC (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
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesC#
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnonoyes infosql, plpgsql, C
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningnoneHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal 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 dataBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
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
Immediate Consistency
Immediate ConsistencyStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDByes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess 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-standardyes
More information provided by the system vendor
Google Cloud BigtableMicrosoft Azure Data ExplorerSadas EngineXTDB infoformerly named CruxYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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More resources
Google Cloud BigtableMicrosoft Azure Data ExplorerSadas EngineXTDB infoformerly named CruxYugabyteDB
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