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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonSphinx  Xexclude from comparisonVoltDB  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 databasesDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelTime Series DBMSSearch engineRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector 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
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websiteiotdb.apache.orgwww.elastic.co/­elasticsearchwww.esgyn.cnsphinxsearch.comwww.voltdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsphinxsearch.com/­docsdocs.voltdb.com
DeveloperApache Software FoundationElasticEsgynSphinx Technologies Inc.VoltDB Inc.
Initial release20182010201520012010
Current release1.1.0, April 20238.6, January 20233.5.1, February 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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++, JavaC++Java, C++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X infofor development
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
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.nonono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyesSQL-like query language (SphinxQL)yes infoonly a subset of SQL 99
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary protocolJava API
JDBC
RESTful HTTP/JSON API
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++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyesyesJava Stored ProceduresnoJava
Triggersyesyes infoby using the 'percolation' featurenonono
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 supportedSharding
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
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkES-Hadoop Connectoryesnono
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 Consistency
Foreign keys infoReferential integritynonoyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesMemcached and Redis integrationno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnoUsers and roles with access to stored procedures

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More resources
Apache IoTDBElasticsearchEsgynDBSphinxVoltDB
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