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DBMS > Bangdb vs. Elasticsearch vs. Kinetica vs. Memcached vs. Vertica

System Properties Comparison Bangdb vs. Elasticsearch vs. Kinetica vs. Memcached vs. Vertica

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonElasticsearch  Xexclude from comparisonKinetica  Xexclude from comparisonMemcached  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA 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 metricFully vectorized database across both GPUs and CPUsIn-memory key-value store, originally intended for cachingCloud 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
Search engineRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series 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
Score132.83
Rank#7  Overall
#1  Search engines
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitebangdb.comwww.elastic.co/­elasticsearchwww.kinetica.comwww.memcached.orgwww.vertica.com
Technical documentationdocs.bangdb.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.kinetica.comgithub.com/­memcached/­memcached/­wikivertica.com/­documentation
DeveloperSachin Sinha, BangDBElasticKineticaDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122010201220032005
Current releaseBangDB 2.0, October 20218.6, January 20237.1, August 20211.6.27, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoElastic LicensecommercialOpen Source infoBSD licensecommercial 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 languageC, C++JavaC, C++CC++
Server operating systemsLinuxAll OS with a Java VMLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeYes, 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, eventsyesyesnoyes
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, geospatialyes infoAll search fields are automatically indexedyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL like support with command line toolSQL-like query languageSQL-like DML and DDL statementsnoFull 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/JSON API
JDBC
ODBC
RESTful HTTP API
Proprietary protocolADO.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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes, Notifications (with Streaming only)yes infoby using the 'percolation' featureyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes, 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 algorithmShardingShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesSource-replica replicationnone infoRepcached, a Memcached patch, provides this functionallityMulti-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 methodsnoES-Hadoop Connectornonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesnoyes
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 integrationyes infoGPU vRAM or System RAMno
User concepts infoAccess controlyes (enterprise version only)Access rights for users and roles on table levelyes infousing SASL (Simple Authentication and Security Layer) protocolfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BangdbElasticsearchKineticaMemcachedVertica 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,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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BangdbElasticsearchKineticaMemcachedVertica infoOpenText™ Vertica™
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