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DBMS > Apache Drill vs. Blueflood vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Drill vs. Blueflood vs. Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonBlueflood  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageScalable TimeSeries DBMS based on CassandraGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsKey-value store
Relational DBMS
Document 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
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedrill.apache.orgblueflood.iocloud.google.com/­bigtablegriddb.netazure.microsoft.com/­services/­data-explorer
Technical documentationdrill.apache.org/­docsgithub.com/­rax-maas/­blueflood/­wikicloud.google.com/­bigtable/­docsdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationRackspaceGoogleToshiba CorporationMicrosoft
Initial release20122013201520132019
Current release1.20.3, January 20235.1, August 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
hostedLinuxhosted
Data schemeschema-freepredefined schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes 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 indexesnononoyesall fields are automatically indexed
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnonoSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsnononoYes, possible languages: KQL, Python, R
Triggersnononoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operationsACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenonoyesno
User concepts infoAccess controlDepending on the underlying data sourcenoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseAzure Active Directory Authentication
More information provided by the system vendor
Apache DrillBluefloodGoogle Cloud BigtableGridDBMicrosoft Azure Data Explorer
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache DrillBluefloodGoogle Cloud BigtableGridDBMicrosoft Azure Data Explorer
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