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

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

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  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.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMS
Primary database modelObject oriented DBMSKey-value store
Wide column store
Wide column storeRelational DBMSGraph 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websiteatoti.iocloud.google.com/­bigtablehbase.apache.orghive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdocs.atoti.iocloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperActiveViamGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookBaidu
Initial release2015200820122018
Current release2.3.4, January 20213.1.3, April 20220.9
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoApache Version 2.0
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 languageJavaJavaJavaJava
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VMLinux
macOS
Unix
Data schemeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROyesyes
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 indexesnonoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLMultidimensional Expressions (MDX)nonoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresPythonnoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobs
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
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
selectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes 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)Immediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsSingle row ACID (across millions of columns)noACID
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.yesnoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesUsers, roles and permissions

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More resources
atotiGoogle Cloud BigtableHBaseHiveHugeGraph
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