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DBMS > Apache IoTDB vs. Elasticsearch vs. EsgynDB vs. Sphinx vs. Vertica

System Properties Comparison Apache IoTDB vs. Elasticsearch vs. EsgynDB vs. Sphinx vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonSphinx  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 FlinkA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOpen source search engine for searching in data from different sources, e.g. relational databasesCloud 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 DBMSSearch engineRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial 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
Score135.35
Rank#7  Overall
#1  Search engines
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteiotdb.apache.orgwww.elastic.co/­elasticsearchwww.esgyn.cnsphinxsearch.comwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsphinxsearch.com/­docsvertica.com/­documentation
DeveloperApache Software FoundationElasticEsgynSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20182010201520012005
Current release1.1.0, April 20238.6, January 20233.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen Source infoGPL version 2, commercial licence availablecommercial 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 languageJavaJavaC++, JavaC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesYes, 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 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.nononono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary protocolADO.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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyesJava Stored Proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infoby using the 'percolation' featurenonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal 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 replicasyesMulti-source replication between multi datacentersnoneMulti-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 SparkES-Hadoop Connectoryesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
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 persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesMemcached and Redis integrationnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBElasticsearchEsgynDBSphinxVertica 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...
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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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Apache IoTDBElasticsearchEsgynDBSphinxVertica infoOpenText™ Vertica™
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