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DBMS > Apache IoTDB vs. BigchainDB vs. Geode vs. Google Cloud Bigtable vs. Sadas Engine

System Properties Comparison Apache IoTDB vs. BigchainDB vs. Geode vs. Google Cloud Bigtable vs. Sadas Engine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  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 FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelTime Series DBMSDocument storeKey-value storeKey-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score1.86
Rank#134  Overall
#24  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websiteiotdb.apache.orgwww.bigchaindb.comgeode.apache.orgcloud.google.com/­bigtablewww.sadasengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestgeode.apache.org/­docscloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software FoundationOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleSADAS s.r.l.
Initial release20182016200220152006
Current release1.1.0, April 20231.1, February 20178.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3Open Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPythonJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedAIX
Linux
Windows
Data schemeyesschema-freeschema-freeschema-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 indexesyesnonoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (OQL)noyes
APIs and other access methodsJDBC
Native API
CLI Client
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyesyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardinghorizontal 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 replicasselectable replication factorMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesyesAccess rights per client and object definableAccess 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-standard

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More resources
Apache IoTDBBigchainDBGeodeGoogle Cloud BigtableSadas Engine
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