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DBMS > Axibase vs. Faircom EDGE vs. Google Cloud Datastore vs. Hypertable vs. Microsoft Azure Data Explorer

System Properties Comparison Axibase vs. Faircom EDGE vs. Google Cloud Datastore vs. Hypertable vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platform
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Document storeWide column storeRelational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.faircom.com/­products/­faircom-edgecloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAxibase CorporationFairCom CorporationGoogleHypertable Inc.Microsoft
Initial release20131979200820092019
Current release15585V3, October 20200.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infoRestricted, free version availablecommercialOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++C++
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
hostedLinux
OS X
Windows infoan inofficial Windows port is available
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyes, ANSI Standard SQL Typesyes, details herenoyes 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.noyesnoyes
Secondary indexesnoyesyesrestricted infoonly exact value or prefix value scansall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesSQL-like query language (GQL)noKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++using Google App EnginenoYes, possible languages: KQL, Python, R
TriggersyesyesCallbacks using the Google Apps Enginenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication using Paxosselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud DataflowyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
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.yesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAzure Active Directory Authentication

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More resources
AxibaseFaircom EDGE infoformerly c-treeEDGEGoogle Cloud DatastoreHypertableMicrosoft Azure Data Explorer
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