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DBMS > Apache IoTDB vs. Faircom DB vs. Hazelcast vs. LMDB

System Properties Comparison Apache IoTDB vs. Faircom DB vs. Hazelcast vs. LMDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHazelcast  Xexclude from comparisonLMDB  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 FlinkNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A widely adopted in-memory data gridA high performant, light-weight, embedded key-value database library
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Key-value storeKey-value 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#164  Overall
#14  Time Series DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score2.09
Rank#121  Overall
#20  Key-value stores
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-dbhazelcast.comwww.symas.com/­symas-embedded-database-lmdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhazelcast.org/­imdg/­docswww.lmdb.tech/­doc
DeveloperApache Software FoundationFairCom CorporationHazelcastSymas
Initial release2018197920082011
Current release1.1.0, April 2023V12, November 20205.3.6, November 20230.9.32, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VMLinux
Unix
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyes, ANSI SQL with proprietary extensionsSQL-like query languageno
APIs and other access methodsJDBC
Native API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Servicesno
Triggersyesyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnone
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, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesFine grained access rights according to SQL-standard with additional protections for filesRole-based access controlno

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More resources
Apache IoTDBFaircom DB infoformerly c-treeACEHazelcastLMDB
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