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DBMS > Firebolt vs. Google Cloud Bigtable vs. QuestDB vs. Sadas Engine

System Properties Comparison Firebolt vs. Google Cloud Bigtable vs. QuestDB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameFirebolt  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuestDB  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseGoogle'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 dataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitewww.firebolt.iocloud.google.com/­bigtablequestdb.iowww.sadasengine.com
Technical documentationdocs.firebolt.iocloud.google.com/­bigtable/­docsquestdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperFirebolt Analytics Inc.GoogleQuestDB Technology IncSADAS s.r.l.
Initial release2020201520142006
Current release8.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree trial version 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
AIX
Linux
Windows
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 indexesyesnonoyes
SQL infoSupport of SQLyesnoSQL with time-series extensionsyes
APIs and other access methods.Net
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
FireboltGoogle Cloud BigtableQuestDBSadas Engine
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
News

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
FireboltGoogle Cloud BigtableQuestDBSadas Engine
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7 September 2022, CTech

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7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
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QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
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QuestDB gets $12M Series A funding amid growing interest in time-series databases
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Read the Pitch Deck Database Startup QuestDB Used to Raise $12 Million
11 November 2021, Business Insider

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provided by Google News



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