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DBMS > Dragonfly vs. Google Cloud Bigtable vs. InterSystems Caché vs. Teradata Aster

System Properties Comparison Dragonfly vs. Google Cloud Bigtable vs. InterSystems Caché vs. Teradata Aster

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application serverPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­bigtablewww.intersystems.com/­products/­cache
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­bigtable/­docsdocs.intersystems.com
DeveloperDragonflyDB team and community contributorsGoogleInterSystemsTeradata
Initial release2023201519972005
Current release1.0, March 20232018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemescheme-freeschema-freedepending on used data modelFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysnoyesyes
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.nonoyesyes infoin Aster File Store
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresLuanoyesR packages
Triggerspublish/subscribe channels provide some trigger functionalitynoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
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 controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
DragonflyGoogle Cloud BigtableInterSystems CachéTeradata Aster
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