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DBMS > Apache IoTDB vs. Memcached vs. Netezza vs. ToroDB vs. Vertica

System Properties Comparison Apache IoTDB vs. Memcached vs. Netezza vs. ToroDB vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMemcached  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonToroDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded 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 FlinkIn-memory key-value store, originally intended for cachingData warehouse and analytics appliance part of IBM PureSystemsA MongoDB-compatible JSON document store, built on top of PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSKey-value storeRelational DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score16.84
Rank#32  Overall
#4  Key-value stores
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websiteiotdb.apache.orgwww.memcached.orgwww.ibm.com/­products/­netezzagithub.com/­torodb/­serverwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­memcached/­memcached/­wikivertica.com/­documentation
DeveloperApache Software FoundationDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalIBM8KdataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20182003200020162005
Current release1.1.0, April 20231.6.29, June 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD licensecommercialOpen Source infoAGPL-V3commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Unix
Windows
Linux infoincluded in applianceAll OS with a Java 7 VMLinux
Data schemeyesschema-freeyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesnoyesyes infostring, integer, double, boolean, date, object_idyes
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.nonono
Secondary indexesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languagenoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
Proprietary protocolJDBC
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingShardinghorizontal partitioning, hierarchical 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 replicasnone infoRepcached, a Memcached patch, provides this functionallitySource-replica replicationSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesyes infousing SASL (Simple Authentication and Security Layer) protocolUsers with fine-grained authorization conceptAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache IoTDBMemcachedNetezza infoAlso called PureData System for Analytics by IBMToroDBVertica infoOpenText™ Vertica™
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