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DBMS > Apache IoTDB vs. Hazelcast vs. HEAVY.AI vs. LevelDB vs. Sadas Engine

System Properties Comparison Apache IoTDB vs. Hazelcast vs. HEAVY.AI vs. LevelDB vs. Sadas Engine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLevelDB  Xexclude from comparisonSadas Engine  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 FlinkA widely adopted in-memory data gridA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelTime Series DBMSKey-value storeRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websiteiotdb.apache.orghazelcast.comgithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­google/­leveldbwww.sadasengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docsdocs.heavy.aigithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software FoundationHazelcastHEAVY.AI, Inc.GoogleSADAS s.r.l.
Initial release20182008201620112006
Current release1.1.0, April 20235.3.6, November 20235.10, January 20221.23, February 20218.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSDcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++ and CUDAC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxIllumos
Linux
OS X
Windows
AIX
Linux
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyes infothe object must implement a serialization strategynonono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesnoyes
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesnonono
Triggersyesyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoRound robinnonehorizontal partitioning
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 infoReplicated MapMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBHazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LevelDBSadas Engine
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