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DBMS > Apache IoTDB vs. Badger vs. Google Cloud Spanner vs. Riak KV vs. Sadas Engine

System Properties Comparison Apache IoTDB vs. Badger vs. Google Cloud Spanner vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A 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.Distributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelTime Series DBMSKey-value storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score0.25
Rank#315  Overall
#46  Key-value stores
Score3.37
Rank#97  Overall
#50  Relational DBMS
Score4.95
Rank#76  Overall
#9  Key-value stores
Score0.06
Rank#371  Overall
#155  Relational DBMS
Websiteiotdb.apache.orggithub.com/­dgraph-io/­badgercloud.google.com/­spannerwww.sadasengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­spanner/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software FoundationDGraph LabsGoogleOpenSource, formerly Basho TechnologiesSADAS s.r.l.
Initial release20182017201720092006
Current release1.1.0, April 20233.2.0, December 20228.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoErlangC++
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
AIX
Linux
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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.nonononono
Secondary indexesyesnoyesrestrictedyes
SQL infoSupport of SQLSQL-like query languagenoyes infoQuery statements complying to ANSI 2011noyes
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
GoGo
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesnonoErlangno
Triggersyesnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding infono "single point of failure"horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneMulti-source replication with 3 replicas for regional instances.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBBadgerGoogle Cloud SpannerRiak KVSadas Engine
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