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DBMS > Apache Druid vs. GBase vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Teradata

System Properties Comparison Apache Druid vs. GBase vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Teradata

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Fully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Relational 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
Graph DBMS
Spatial DBMS
Time Series DBMS
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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedruid.apache.orgwww.gbase.cnazure.microsoft.com/­services/­data-explorersqrrl.comwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.teradata.com
DeveloperApache Software Foundation and contributorsGeneral Data Technology Co., Ltd.MicrosoftAmazon infooriginally Sqrrl Data, Inc.Teradata
Initial release20122004201920121984
Current release29.0.1, April 2024GBase 8a, GBase 8s, GBase 8ccloud service with continuous releasesTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, PythonJava
Server operating systemsLinux
OS X
Unix
LinuxhostedLinuxhosted
Linux
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.noyesyesyes
Secondary indexesyesyesall fields are automatically indexedyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL for queryingStandard with numerous extensionsKusto Query Language (KQL), SQL subsetnoyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
C API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Rnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of HadoopMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoAtomic updates per row, document, or graph entityACID
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
Apache DruidGBaseMicrosoft Azure Data ExplorerSqrrlTeradata
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