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DBMS > Dragonfly vs. Google Cloud Spanner vs. Splice Machine vs. Teradata Aster

System Properties Comparison Dragonfly vs. Google Cloud Spanner vs. Splice Machine vs. Teradata Aster

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
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 instanceA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­spannersplicemachine.com
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­spanner/­docssplicemachine.com/­how-it-works
DeveloperDragonflyDB team and community contributorsGoogleSplice MachineTeradata
Initial release2023201720142005
Current release1.0, March 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux
Data schemescheme-freeyesyesFlexible 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 arraysyesyesyes
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.nonoyes infoin Aster File Store
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011yesyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
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
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresLuanoyes infoJavaR packages
Triggerspublish/subscribe channels provide some trigger functionalitynoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
yes 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 methodsnoyes infousing Google Cloud DataflowYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infoStrict serializable isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyes, multi-version concurrency control (MVCC)yes
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 roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DragonflyGoogle Cloud SpannerSplice MachineTeradata Aster
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