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DBMS > Apache IoTDB vs. EJDB vs. Faircom EDGE vs. Kyligence Enterprise vs. Sqrrl

System Properties Comparison Apache IoTDB vs. EJDB vs. Faircom EDGE vs. Kyligence Enterprise vs. Sqrrl

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonKyligence Enterprise  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 FlinkEmbeddable document-store database library with JSON representation of queries (in MongoDB style)FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA distributed analytics engine for big data, built on top of Apache KylinAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSDocument storeKey-value store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Websiteiotdb.apache.orggithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgekyligence.io/­kyligence-enterprisesqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperApache Software FoundationSoftmotionsFairCom CorporationKyligence, Inc.Amazon infooriginally Sqrrl Data, Inc.
Initial release20182012197920162012
Current release1.1.0, April 2023V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCANSI C, C++JavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)server-lessAndroid
Linux infoARM, x86
Raspbian
Windows
LinuxLinux
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, ANSI Standard SQL 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.noyesno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infoANSI SQL queriesANSI SQL for queries (using Apache Calcite)no
APIs and other access methodsJDBC
Native API
in-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesnoyes info.Net, JavaScript, C/C++no
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneFile partitioning infoCustomizable business rules for partitioningSharding 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 replicasnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBEJDBFaircom EDGE infoformerly c-treeEDGEKyligence EnterpriseSqrrl
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