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DBMS > Datomic vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. QuestDB

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. QuestDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Microsofts flagship relational DBMSA high performance open source SQL database for time series data
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­bigtablewww.microsoft.com/­en-us/­sql-serverquestdb.io
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-US/­sql/­sql-serverquestdb.io/­docs
DeveloperCognitectGoogleMicrosoftQuestDB Technology Inc
Initial release2012201519892014
Current release1.0.6735, June 2023SQL Server 2022, November 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJava, ClojureC++Java (Zero-GC), C++, Rust
Server operating systemsAll OS with a Java VMhostedLinux
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLnonoyesSQL with time-series extensions
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingtables can be distributed across several files (horizontal partitioning); sharding through federationhorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesyes, but depending on the SQL-Server EditionSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes infothrough memory mapped files
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard
More information provided by the system vendor
DatomicGoogle Cloud BigtableMicrosoft SQL ServerQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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DatomicGoogle Cloud BigtableMicrosoft SQL ServerQuestDB
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