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DBMS > Firebolt vs. GeoSpock vs. Google Cloud Datastore vs. Quasardb vs. TimescaleDB

System Properties Comparison Firebolt vs. GeoSpock vs. Google Cloud Datastore vs. Quasardb vs. TimescaleDB

Editorial information provided by DB-Engines
NameFirebolt  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseSpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, high-performance timeseries databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSTime Series DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.firebolt.iogeospock.comcloud.google.com/­datastorequasar.aiwww.timescale.com
Technical documentationdocs.firebolt.iocloud.google.com/­datastore/­docsdoc.quasar.ai/­masterdocs.timescale.com
DeveloperFirebolt Analytics Inc.GeoSpockGooglequasardbTimescale
Initial release2020200820092017
Current release2.0, September 20193.14.1, January 20242.15.0, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++C
Server operating systemshostedhostedhostedBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyestemporal, categoricalyesyes infowith tagsyes
SQL infoSupport of SQLyesANSI SQL for query only (using Presto)SQL-like query language (GQL)SQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methods.Net
ODBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonousing Google App Enginenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnonoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerMulti-source replication using PaxosSource-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowwith Hadoop integrationno
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient modeno
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)Cryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
FireboltGeoSpockGoogle Cloud DatastoreQuasardbTimescaleDB
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