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DBMS > Amazon Redshift vs. Apache Druid vs. Google Cloud Bigtable vs. Transwarp Hippo

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Google Cloud Bigtable vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Druid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.25
Rank#38  Overall
#23  Relational DBMS
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.00
Rank#385  Overall
#16  Vector DBMS
Websiteaws.amazon.com/­redshiftdruid.apache.orgcloud.google.com/­bigtablewww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationdocs.aws.amazon.com/­redshiftdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigtable/­docs
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation and contributorsGoogle
Initial release2012201220152023
Current release30.0.0, June 20241.0, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC++
Server operating systemshostedLinux
OS X
Unix
hostedLinux
macOS
Data schemeyesyes infoschema-less columns are supportedschema-free
Typing infopredefined data types such as float or dateyesyesnoVector, Numeric and String
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.nononono
Secondary indexesrestrictedyesnono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL for queryingnono
APIs and other access methodsJDBC
ODBC
JDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rights

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More resources
Amazon RedshiftApache DruidGoogle Cloud BigtableTranswarp Hippo
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