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

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

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonCrateDB  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDistributed Database based on LucenedBase 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.Fully managed big data interactive analytics platform
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value store
Wide column store
Relational DBMS infocolumn oriented
Secondary database modelsRelational DBMSDocument 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
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score10.34
Rank#44  Overall
#28  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financecratedb.comwww.dbase.comcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorer
Technical documentationcratedb.com/­docswww.dbase.com/­support/­knowledgebasecloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAxibase CorporationCrateAsthon TateGoogleMicrosoft
Initial release20132013197920152019
Current release15585dBASE 2019, 2019cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJava
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportDOS infodBase Classic
Windows infodBase Pro
hostedhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyesnoyes 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.nononoyes
Secondary indexesnoyesyesnoall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitynonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
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)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
PHP
Python
R
Ruby
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
dBase proprietary IDEC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)no infoThe IDE can access stored procedures in other database systems.noYes, possible languages: KQL, Python, R
Triggersyesnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyno infonot for dBase internal data, but IDE does support transactions when accessing external DBMSAtomic single-row operationsno
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.nonono
User concepts infoAccess controlrights management via user accountsAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authentication
More information provided by the system vendor
AxibaseCrateDBdBASEGoogle Cloud BigtableMicrosoft Azure Data Explorer
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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AxibaseCrateDBdBASEGoogle Cloud BigtableMicrosoft Azure Data Explorer
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