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DBMS > Apache IoTDB vs. Databricks vs. EDB Postgres vs. HarperDB

System Properties Comparison Apache IoTDB vs. Databricks vs. EDB Postgres vs. HarperDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonHarperDB  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 FlinkThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelTime Series DBMSDocument store
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Websiteiotdb.apache.orgwww.databricks.comwww.enterprisedb.comwww.harperdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comwww.enterprisedb.com/­docsdocs.harperdb.io/­docs
DeveloperApache Software FoundationDatabricksEnterpriseDBHarperDB
Initial release2018201320052017
Current release1.1.0, April 202314, December 20213.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoBSD for PostgreSQL-componentscommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCNode.js
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
Windows
Linux
OS X
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesdynamic schema
Typing infopredefined data types such as float or dateyesyesyes infoJSON data types
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.noyesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLyes infostandard with numerous extensionsSQL-like data manipulation statements
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.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
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Custom Functions infosince release 3.1
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoby hash, list or rangeA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replicationyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
Apache IoTDBDatabricksEDB PostgresHarperDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IoTDBDatabricksEDB PostgresHarperDB
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