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DBMS > GeoSpock vs. Google Cloud Bigtable vs. QuestDB vs. Vitess

System Properties Comparison GeoSpock vs. Google Cloud Bigtable vs. QuestDB vs. Vitess

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Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuestDB  Xexclude from comparisonVitess  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high performance open source SQL database for time series dataScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitegeospock.comcloud.google.com/­bigtablequestdb.iovitess.io
Technical documentationcloud.google.com/­bigtable/­docsquestdb.io/­docsvitess.io/­docs
DeveloperGeoSpockGoogleQuestDB Technology IncThe Linux Foundation, PlanetScale
Initial release201520142013
Current release2.0, September 201915.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses 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, JavascriptJava (Zero-GC), C++, RustGo
Server operating systemshostedhostedLinux
macOS
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyes infoschema-free via InfluxDB Line Protocolyes
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.nonono
Secondary indexestemporal, categoricalnonoyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)noSQL with time-series extensionsyes infowith proprietary extensions
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononoyes infoproprietary syntax
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with eventual consistencyMulti-source replication
Source-replica replication
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID for single-table writesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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 filesyes
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
GeoSpockGoogle Cloud BigtableQuestDBVitess
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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More resources
GeoSpockGoogle Cloud BigtableQuestDBVitess
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