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DBMS > Datastax Enterprise vs. FileMaker vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. OrigoDB

System Properties Comparison Datastax Enterprise vs. FileMaker vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. OrigoDB

Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonFileMaker  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Distributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformA fully ACID in-memory object graph database
Primary database modelWide column storeRelational DBMSEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedDocument store
Object oriented DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector 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
Score5.80
Rank#60  Overall
#4  Wide column stores
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websitewww.datastax.com/­products/­datastax-enterprisewww.claris.com/­filemakerwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerorigodb.com
Technical documentationdocs.datastax.comwww.claris.com/­resources/­documentationwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docs
DeveloperDataStaxClaris infoa subsidiary of AppleIBMMicrosoftRobert Friberg et al
Initial release20111983201720192009 infounder the name LiveDB
Current release6.8, April 202019.4.1, November 20212.0cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availablecommercialOpen Source
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.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaC and C++C#
Server operating systemsLinux
OS X
iOS infoclient part only
Linux
OS X
Windows
Linux infoLinux, macOS, Windows for the developer additionhostedLinux
Windows
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesUser defined using .NET types and collections
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.noyes infoA http query request can return the data in XML formatnoyesno infocan be achieved using .NET
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLyes infovia pluginsyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetno
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Filemaker WebDirect
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
PHPC
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
Server-side scripts infoStored proceduresnoyesyesYes, possible languages: KQL, Python, Ryes
Triggersyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"noneShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingSource-replica replication, warm standby infosince Version 14Active-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per objectsimple rights management via user accounts and connection to external directory servicesfine grained access rights according to SQL-standardAzure Active Directory AuthenticationRole based authorization
More information provided by the system vendor
Datastax EnterpriseFileMakerIBM Db2 Event StoreMicrosoft Azure Data ExplorerOrigoDB
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Datastax EnterpriseFileMakerIBM Db2 Event StoreMicrosoft Azure Data ExplorerOrigoDB
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