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DBMS > Apache IoTDB vs. BigObject vs. Google Cloud Datastore vs. Sqrrl

System Properties Comparison Apache IoTDB vs. BigObject vs. Google Cloud Datastore vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
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 FlinkAnalytic DBMS for real-time computations and queriesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedDocument storeDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websiteiotdb.apache.orgbigobject.iocloud.google.com/­datastoresqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iocloud.google.com/­datastore/­docs
DeveloperApache Software FoundationBigObject, Inc.GoogleAmazon infooriginally Sqrrl Data, Inc.
Initial release2018201520082012
Current release1.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (GQL)no
APIs and other access methodsJDBC
Native API
fluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesLuausing Google App Engineno
TriggersyesnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding infomaking use of Hadoop
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 using Paxosselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesyesno
User concepts infoAccess controlyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBBigObjectGoogle Cloud DatastoreSqrrl
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