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DBMS > Datastax Enterprise vs. Google Cloud Bigtable vs. Graphite vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison Datastax Enterprise vs. Google Cloud Bigtable vs. Graphite vs. Kinetica vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraphite  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelWide column storeKey-value store
Wide column store
Time Series DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Spatial DBMS
Time Series 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisecloud.google.com/­bigtablegithub.com/­graphite-project/­graphite-webwww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.datastax.comcloud.google.com/­bigtable/­docsgraphite.readthedocs.iodocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDataStaxGoogleChris DavisKineticaMicrosoft
Initial release20112015200620122019
Current release6.8, April 20207.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
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 languageJavaPythonC, C++
Server operating systemsLinux
OS X
hostedLinux
Unix
Linuxhosted
Data schemeschema-freeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesyesnonoyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLnonoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Sockets
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononouser defined functionsYes, possible languages: KQL, Python, R
Triggersyesnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingnoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsAtomic single-row operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infolockingyesyes
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.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles on table levelAzure Active Directory Authentication
More information provided by the system vendor
Datastax EnterpriseGoogle Cloud BigtableGraphiteKineticaMicrosoft Azure Data Explorer
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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Datastax EnterpriseGoogle Cloud BigtableGraphiteKineticaMicrosoft Azure Data Explorer
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