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DBMS > atoti vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. TDengine

System Properties Comparison atoti vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. TDengine

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSTime Series DBMS and big data platform
Primary database modelObject oriented DBMSKey-value store
Wide column store
Relational DBMSGraph DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteatoti.iocloud.google.com/­bigtablehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
github.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.atoti.iocloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docsdocs.tdengine.com
DeveloperActiveViamGoogleApache Software Foundation infoinitially developed by FacebookBaiduTDEngine, previously Taos Data
Initial release2015201220182019
Current release3.1.3, April 20220.93.0, August 2022
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaC
Server operating systemshostedAll OS with a Java VMLinux
macOS
Unix
Linux
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like DML and DDL statementsnoStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Groovy
Java
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresPythonnoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsno
Triggersnononoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducevia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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
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 rolesUsers, roles and permissionsyes
More information provided by the system vendor
atotiGoogle Cloud BigtableHiveHugeGraphTDengine
Specific characteristicsTDengineā„¢ 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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More resources
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