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DBMS > Datomic vs. Google Cloud Bigtable vs. Hive vs. Quasardb

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Hive vs. Quasardb

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle'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 HadoopDistributed, high-performance timeseries database
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­bigtablehive.apache.orgquasar.ai
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedoc.quasar.ai/­master
DeveloperCognitectGoogleApache Software Foundation infoinitially developed by Facebookquasardb
Initial release2012201520122009
Current release1.0.6735, June 20233.1.3, April 20223.14.1, January 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC++
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VMBSD
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infointeger and binary
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 indexesyesnoyesyes infowith tags
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
HTTP API
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infouser defined functions and integration of map-reduceno
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factorSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducewith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes infoTransient mode
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesCryptographically strong user authentication and audit trail

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DatomicGoogle Cloud BigtableHiveQuasardb
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