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DBMS > BigObject vs. Google Cloud Bigtable vs. QuestDB vs. TDengine

System Properties Comparison BigObject vs. Google Cloud Bigtable vs. QuestDB vs. TDengine

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuestDB  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesGoogle'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 dataTime Series DBMS and big data platform
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Wide column store
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitebigobject.iocloud.google.com/­bigtablequestdb.iogithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docsquestdb.io/­docsdocs.tdengine.com
DeveloperBigObject, Inc.GoogleQuestDB Technology IncTDEngine, previously Taos Data
Initial release2015201520142019
Current release3.0, August 2022
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
macOS
Windows
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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL with time-series extensionsStandard SQL with extensions for time-series applications
APIs and other access methodsfluentd
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
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresLuanonono
Triggersnononoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with eventual consistencyyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnoyes infothrough memory mapped files
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
BigObjectGoogle Cloud BigtableQuestDBTDengine
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
TDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
BigObjectGoogle Cloud BigtableQuestDBTDengine
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