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DBMS > Apache Druid vs. Google Cloud Bigtable vs. Hive vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Apache Druid vs. Google Cloud Bigtable vs. Hive vs. Microsoft Azure Data Explorer vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Relational DBMSRelational DBMS infocolumn orientedKey-value 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgcloud.google.com/­bigtablehive.apache.orgazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsGoogleApache Software Foundation infoinitially developed by FacebookMicrosoftSimer Plaha
Initial release20122015201220192018
Current release29.0.1, April 20243.1.3, April 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2commercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VMhosted
Data schemeyes infoschema-less columns are supportedschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonoyesno
Secondary indexesyesnoyesall fields are automatically indexedno
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Rno
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
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 ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnonoAtomic execution of operations
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.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesAzure Active Directory Authenticationno

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More resources
Apache DruidGoogle Cloud BigtableHiveMicrosoft Azure Data ExplorerSwayDB
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