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DBMS > Apache IoTDB vs. Graph Engine vs. HEAVY.AI vs. Tarantool vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. HEAVY.AI vs. Tarantool vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonTarantool  Xexclude from comparisonTimescaleDB  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsSpatial DBMSSpatial DBMS infowith Tarantool/GIS extensionRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgwww.graphengine.iogithub.com/­heavyai/­heavydb
www.heavy.ai
www.tarantool.iowww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.heavy.aiwww.tarantool.io/­en/­docdocs.timescale.com
DeveloperApache Software FoundationMicrosoftHEAVY.AI, Inc.VKTimescale
Initial release20182010201620082017
Current release1.1.0, April 20235.10, January 20222.10.0, May 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CC++ and CUDAC and C++C
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinuxBSD
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.nonononoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoyesFull-featured ANSI SQL supportyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
Open binary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyesnoLua, C and SQL stored proceduresuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnonoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding infoRound robinSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication with hot standby and reads on replicas info
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 ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022TarantoolTimescaleDB
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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