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DBMS > FileMaker vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. RisingWave vs. SingleStore

System Properties Comparison FileMaker vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. RisingWave vs. SingleStore

Editorial information provided by DB-Engines
NameFileMaker  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRisingWave  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionFileMaker is a cross-platform RDBMS that includes a GUI frontend.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 platformA distributed RDBMS for stream processing, wire-compatible with PostgreSQLMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMSRelational DBMS
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
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Websitewww.claris.com/­filemakercloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerwww.risingwave.com/­databasewww.singlestore.com
Technical documentationwww.claris.com/­resources/­documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.risingwave.com/­docs/­current/­introdocs.singlestore.com
DeveloperClaris infoa subsidiary of AppleGoogleMicrosoftRisingWave LabsSingleStore Inc.
Initial release19832015201920222013
Current release19.4.1, November 2021cloud service with continuous releases1.2, September 20238.5, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageRustC++, Go
Server operating systemsiOS infoclient part only
Linux
OS X
Windows
hostedhostedDocker
Linux
macOS
Linux info64 bit version required
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesStandard SQL-types and JSONyes
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.yes infoA http query request can return the data in XML formatnoyesnono
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLyes infovia pluginsnoKusto Query Language (KQL), SQL subsetyesyes infobut no triggers and foreign keys
APIs and other access methodsFilemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
PostgreSQL wire protocol
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesPHPC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, RUDFs in Python or Javayes
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication, warm standby infosince Version 14Internal 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.Source-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlsimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory AuthenticationUsers and RolesFine grained access control via users, groups and roles
More information provided by the system vendor
FileMakerGoogle Cloud BigtableMicrosoft Azure Data ExplorerRisingWaveSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
FileMakerGoogle Cloud BigtableMicrosoft Azure Data ExplorerRisingWaveSingleStore infoformer name was MemSQL
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