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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  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 FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSDocument storeKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Websiteiotdb.apache.orgcloud.google.com/­datastorehazelcast.comsqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docs
DeveloperApache Software FoundationGoogleHazelcastAmazon infooriginally Sqrrl Data, Inc.
Initial release2018200820082012
Current release1.1.0, April 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll OS with a Java VMLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP 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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesusing Google App Engineyes infoEvent Listeners, Executor Servicesno
TriggersyesCallbacks using the Google Apps Engineyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding 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 replicasMulti-source replication using Paxosyes infoReplicated Mapselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflowyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate 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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBGoogle Cloud DatastoreHazelcastSqrrl
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