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DBMS > Apache IoTDB vs. HarperDB vs. Microsoft Access vs. Sqrrl

System Properties Comparison Apache IoTDB vs. HarperDB vs. Microsoft Access vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Access  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 FlinkHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSDocument storeRelational DBMSDocument 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
Score0.55
Rank#243  Overall
#38  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgwww.harperdb.iowww.microsoft.com/­en-us/­microsoft-365/­accesssqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationHarperDBMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2018201719922012
Current release1.1.0, April 20233.1, August 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoNot a real database server, but making use of DLLsLinux
Data schemeyesdynamic schemayesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsyes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
DAO
ODBC
OLE DB
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1yes infosince Access 2010 using the ACE-engineno
Triggersyesnoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)A table resides as a whole on one (or more) nodes in a clusternoneSharding 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 replicasyes infothe nodes on which a table resides can be definednoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infobut no files for transaction loggingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesAccess rights for users and rolesno infoa simple user-level security was built in till version Access 2003Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBHarperDBMicrosoft AccessSqrrl
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