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DBMS > Hypertable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. RavenDB vs. TerarkDB

System Properties Comparison Hypertable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. RavenDB vs. TerarkDB

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  Xexclude from comparisonTerarkDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopDistributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelWide column storeEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedDocument storeKey-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
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerravendb.netgithub.com/­bytedance/­terarkdb
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperHypertable Inc.IBMMicrosoftHibernating RhinosByteDance, originally Terark
Initial release20092017201920102016
Current release0.9.8.11, March 20162.0cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availablecommercialOpen Source infoAGPL version 3, commercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C#C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoLinux, macOS, Windows for the developer additionhostedLinux
macOS
Raspberry Pi
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnono
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.noyesno
Secondary indexesrestricted infoonly exact value or prefix value scansnoall fields are automatically indexedyesno
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)no
APIs and other access methodsC++ API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
C++ API
Java API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Ryesno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelActive-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory AuthenticationAuthorization levels configured per client per databaseno

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More resources
HypertableIBM Db2 Event StoreMicrosoft Azure Data ExplorerRavenDBTerarkDB
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