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DBMS > DolphinDB vs. GeoMesa vs. Google Cloud Spanner vs. Microsoft SQL Server vs. Tkrzw

System Properties Comparison DolphinDB vs. GeoMesa vs. Google Cloud Spanner vs. Microsoft SQL Server vs. Tkrzw

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Microsofts flagship relational DBMSA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSSpatial DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.dolphindb.comwww.geomesa.orgcloud.google.com/­spannerwww.microsoft.com/­en-us/­sql-serverdbmx.net/­tkrzw
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­spanner/­docslearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperDolphinDB, IncCCRi and othersGoogleMicrosoftMikio Hirabayashi
Initial release20182014201719892020
Current releasev2.00.4, January 20225.0.0, May 2024SQL Server 2022, November 20220.9.3, August 2020
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoApache License 2.0commercialcommercial inforestricted free version is availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++ScalaC++C++
Server operating systemsLinux
Windows
hostedLinux
Windows
Linux
macOS
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infoQuery statements complying to ANSI 2011yesno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Go
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnonoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningdepending on storage layerShardingtables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesdepending on storage layerMulti-source replication with 3 replicas for regional instances.yes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layerImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoStrict serializable isolationACID
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.yesdepending on storage layernoyesyes infousing specific database classes
User concepts infoAccess controlAdministrators, Users, Groupsyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
DolphinDBGeoMesaGoogle Cloud SpannerMicrosoft SQL ServerTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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