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DBMS > Apache IoTDB vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Vertica

System Properties Comparison Apache IoTDB vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
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 FlinkHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A 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 metricElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerCloud 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 DBMSGraph DBMS
RDF store
Search engineRelational DBMSRelational 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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score132.83
Rank#7  Overall
#1  Search engines
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteiotdb.apache.orgblazegraph.comwww.elastic.co/­elasticsearchazure.microsoft.com/­services/­synapse-analyticswww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwiki.blazegraph.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticsvertica.com/­documentation
DeveloperApache Software FoundationBlazegraphElasticMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20182006201020162005
Current release1.1.0, April 20232.1.5, March 20198.6, January 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoextended commercial license availableOpen Source infoElastic Licensecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononoyesno 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 languageJavaJavaJavaC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
All OS with a Java VMhostedLinux
Data schemeyesschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesYes, 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 dateyesyes infoRDF literal typesyesyesyes
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 indexesyesyesyes infoAll search fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageSPARQL is used as query languageSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
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++
Java
JavaScript
PHP
Python
Ruby
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyesyesTransact SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes infoby using the 'percolation' featurenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding, horizontal partitioninghorizontal 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 replicasyesyesyesMulti-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 SparknoES-Hadoop Connectornono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationEventual 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 integritynoyes infoRelationships in Graphsnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
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.yesMemcached and Redis integrationno
User concepts infoAccess controlyesSecurity and Authentication via Web Application Container (Tomcat, Jetty)yesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBBlazegraphElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica 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...
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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 IoTDBBlazegraphElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica infoOpenText™ Vertica™
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