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DBMS > Databricks vs. Google Cloud Datastore vs. QuestDB vs. STSdb

System Properties Comparison Databricks vs. Google Cloud Datastore vs. QuestDB vs. STSdb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance open source SQL database for time series dataKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Relational DBMS
Document storeTime Series DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.databricks.comcloud.google.com/­datastorequestdb.iogithub.com/­STSSoft/­STSdb4
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsquestdb.io/­docs
DeveloperDatabricksGoogleQuestDB Technology IncSTS Soft SC
Initial release2013200820142011
Current release4.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava (Zero-GC), C++, RustC#
Server operating systemshostedhostedLinux
macOS
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infoprimitive types and user defined types (classes)
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.yesnono
Secondary indexesyesyesnono
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)SQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
.NET Client API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C#
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Enginenono
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreQuestDBSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational 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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