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DBMS > Apache IoTDB vs. Databend vs. Hawkular Metrics vs. TimescaleDB vs. Vertica

System Properties Comparison Apache IoTDB vs. Databend vs. Hawkular Metrics vs. TimescaleDB vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A time series DBMS optimized for fast ingest and complex queries, based on 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 DBMSRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.hawkular.orgwww.timescale.comwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.comvertica.com/­documentation
DeveloperApache Software FoundationDatabend LabsCommunity supported by Red HatTimescaleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20182021201420172005
Current release1.1.0, April 20231.0.59, April 20232.15.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0commercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJavaCC++
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesschema-freeyesYes, 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 dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nononoyesno
Secondary indexesyesnonoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyesnoyes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
RESTful HTTP API
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
Go
Java
JavaScript (Node.js)
Python
Rust
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes infovia Hawkular Alertingyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infobased on Cassandrayes, across time and space (hash partitioning) attributeshorizontal 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 replicasnoneselectable replication factor infobased on CassandraSource-replica replication with hot standby and reads on replicas infoMulti-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 Sparknononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlyesUsers with fine-grained authorization concept, user rolesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBDatabendHawkular MetricsTimescaleDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache IoTDBDatabendHawkular MetricsTimescaleDBVertica infoOpenText™ Vertica™
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