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DBMS > Bangdb vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Vertica

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

Editorial information provided by DB-Engines
NameBangdb  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.
DescriptionConverged and high performance database for device data, events, time series, document and graphHigh-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 modelDocument store
Graph DBMS
Time Series DBMS
Graph DBMS
RDF store
Search engineRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  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
Websitebangdb.comblazegraph.comwww.elastic.co/­elasticsearchazure.microsoft.com/­services/­synapse-analyticswww.vertica.com
Technical documentationdocs.bangdb.comwiki.blazegraph.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticsvertica.com/­documentation
DeveloperSachin Sinha, BangDBBlazegraphElasticMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122006201020162005
Current releaseBangDB 2.0, October 20212.1.5, March 20198.6, January 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open 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 languageC, C++JavaJavaC++C++
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VMhostedLinux
Data schemeschema-freeschema-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 dateyes: string, long, double, int, geospatial, stream, eventsyes 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 indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infoAll search fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL like support with command line toolSPARQL is used as query languageSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsProprietary protocol
RESTful HTTP 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++
Java
Python
.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 proceduresnoyesyesTransact SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes, Notifications (with Streaming only)noyes infoby using the 'percolation' featurenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding, horizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesyesyesMulti-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 methodsnonoES-Hadoop Connectornono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate 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 dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeMemcached and Redis integrationno
User concepts infoAccess controlyes (enterprise version only)Security 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
BangdbBlazegraphElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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BangdbBlazegraphElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica infoOpenText™ Vertica™
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