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DBMS > Axibase vs. dBASE vs. Google Cloud Bigtable vs. GridGain vs. Microsoft Azure Data Explorer

System Properties Comparison Axibase vs. dBASE vs. Google Cloud Bigtable vs. GridGain vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationdBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platform
Primary database modelTime Series DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Relational 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
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score10.34
Rank#44  Overall
#28  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.dbase.comcloud.google.com/­bigtablewww.gridgain.comazure.microsoft.com/­services/­data-explorer
Technical documentationwww.dbase.com/­support/­knowledgebasecloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAxibase CorporationAsthon TateGoogleGridGain Systems, Inc.Microsoft
Initial release20131979201520072019
Current release15585dBASE 2019, 2019GridGain 8.5.1cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialcommercialcommercial
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 languageJavaJava, C++, .Net
Server operating systemsLinuxDOS infodBase Classic
Windows infodBase Pro
hostedLinux
OS X
Solaris
Windows
hosted
Data schemeyesyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesnoyesyes 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.nonoyesyes
Secondary indexesnoyesnoyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
none infoThe IDE can access other DBMS or ODBC-sources.gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
PHP
Python
R
Ruby
dBase proprietary IDEC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesno infoThe IDE can access stored procedures in other database systems.noyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersyesnonoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infonot for dBase internal data, but IDE does support transactions when accessing external DBMSAtomic single-row operationsACIDno
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.noyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAzure Active Directory Authentication

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More resources
AxibasedBASEGoogle Cloud BigtableGridGainMicrosoft Azure Data Explorer
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