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DBMS > Google Cloud Bigtable vs. Informix vs. Oracle Rdb vs. TDengine

System Properties Comparison Google Cloud Bigtable vs. Informix vs. Oracle Rdb vs. TDengine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInformix  Xexclude from comparisonOracle Rdb  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataTime Series DBMS and big data platform
Primary database modelKey-value store
Wide column store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­informixwww.oracle.com/­database/­technologies/­related/­rdb.htmlgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationcloud.google.com/­bigtable/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
www.oracle.com/­database/­technologies/­related/­rdb-doc.htmldocs.tdengine.com
DeveloperGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Oracle, originally developed by Digital Equipment Corporation (DEC)TDEngine, previously Taos Data
Initial release2015198419842019
Current release14.10.FC5, November 20207.4.1.1, 20213.0, August 2022
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercialOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and JavaC
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
HP Open VMSLinux
Windows
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or datenoyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesyesStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yes
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 integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDyes, on a single node
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authentication, authorization, and auditing controlsyes
More information provided by the system vendor
Google Cloud BigtableInformixOracle RdbTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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