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DBMS > Apache Kylin vs. etcd vs. HBase vs. Microsoft Azure Data Explorer vs. SingleStore

System Properties Comparison Apache Kylin vs. etcd vs. HBase vs. Microsoft Azure Data Explorer vs. SingleStore

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platformMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMS infocolumn orientedRelational 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
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.38
Rank#62  Overall
#35  Relational DBMS
Websitekylin.apache.orgetcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgazure.microsoft.com/­services/­data-explorerwww.singlestore.com
Technical documentationkylin.apache.org/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.singlestore.com
DeveloperApache Software Foundation, originally contributed from eBay IncApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftSingleStore Inc.
Initial release2015200820192013
Current release3.1.0, July 20203.4, August 20192.3.4, January 2021cloud service with continuous releases8.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache version 2commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaGoJavaC++, Go
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
hostedLinux info64 bit version required
Data schemeyesschema-freeschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyesno
Secondary indexesyesnonoall fields are automatically indexedyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nonoKusto Query Language (KQL), SQL subsetyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaYes, possible languages: KQL, Python, Ryes
Triggersyes, watching key changesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnoyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory AuthenticationFine grained access control via users, groups and roles
More information provided by the system vendor
Apache KylinetcdHBaseMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
Apache KylinetcdHBaseMicrosoft Azure Data ExplorerSingleStore infoformer name was MemSQL
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