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DBMS > Datastax Enterprise vs. Google Cloud Bigtable vs. Hive

System Properties Comparison Datastax Enterprise vs. Google Cloud Bigtable vs. Hive

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Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.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 Hadoop
Primary database modelWide column storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.31
Rank#57  Overall
#4  Wide column stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Websitewww.datastax.com/­products/­datastax-enterprisecloud.google.com/­bigtablehive.apache.org
Technical documentationdocs.datastax.comcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDataStaxGoogleApache Software Foundation infoinitially developed by Facebook
Initial release201120152012
Current release6.8, April 20203.1.3, April 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJava
Server operating systemsLinux
OS X
hostedAll OS with a Java VM
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLnoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduce
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
Datastax EnterpriseGoogle Cloud BigtableHive
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Datastax EnterpriseGoogle Cloud BigtableHive
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