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DBMS > Badger vs. Datastax Enterprise vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. SpaceTime

System Properties Comparison Badger vs. Datastax Enterprise vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. SpaceTime

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpaceTime  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.DataStax 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.Common in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelKey-value storeWide column storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedSpatial DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score5.93
Rank#56  Overall
#4  Wide column stores
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datastax.com/­products/­datastax-enterprisewww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorerwww.mireo.com/­spacetime
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datastax.comwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDGraph LabsDataStaxIBMMicrosoftMireo
Initial release201720111983 infohost version20192020
Current release6.8, April 202012.1, October 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree version is availablecommercialcommercial
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 languageGoJavaC and C++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
AIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datenoyesyesyes 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.nonoyesno
Secondary indexesnoyesyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL); Spark SQLyesKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGoC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Python
Server-side scripts infoStored proceduresnonoyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infono "single point of failure"Sharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceFixed-grid hypercubes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Real-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDnono
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.noyesnono
User concepts infoAccess controlnoAccess rights for users can be defined per objectfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes
More information provided by the system vendor
BadgerDatastax EnterpriseIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSpaceTime
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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BadgerDatastax EnterpriseIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSpaceTime
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