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DBMS > atoti vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. Microsoft Azure Table Storage

System Properties Comparison atoti vs. Google Cloud Bigtable vs. Hive vs. HugeGraph vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Table Storage  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 DBMSA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelObject oriented DBMSKey-value store
Wide column store
Relational DBMSGraph DBMSWide column store
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteatoti.iocloud.google.com/­bigtablehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.atoti.iocloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperActiveViamGoogleApache Software Foundation infoinitially developed by FacebookBaiduMicrosoft
Initial release2015201220182012
Current release3.1.3, April 20220.9
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemshostedAll OS with a Java VMLinux
macOS
Unix
hosted
Data schemeschema-freeyesyesschema-free
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 statementsnono
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
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Groovy
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresPythonnoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud service
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 infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducevia hugegraph-sparkno
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDoptimistic locking
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.yesnoyesno
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 permissionsAccess rights based on private key authentication or shared access signatures

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More resources
atotiGoogle Cloud BigtableHiveHugeGraphMicrosoft Azure Table Storage
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