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DBMS > Apache Impala vs. Bangdb vs. Memgraph vs. Solr

System Properties Comparison Apache Impala vs. Bangdb vs. Memgraph vs. Solr

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonMemgraph  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphAn open source graph database built for real-time streaming and compatible with Neo4jA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Graph DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score3.19
Rank#94  Overall
#8  Graph DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgbangdb.commemgraph.comsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.commemgraph.com/­docssolr.apache.org/­resources.html
Social network pagesLinkedInTwitterFacebookGitHubDiscord
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBMemgraph LtdApache Software Foundation
Initial release2013201220172006
Current release4.1.0, June 2022BangDB 2.0, October 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD 3Open Source infoBSL 1.1; commercial license for enterprise edition availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++C and C++Java
Server operating systemsLinuxLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-free and schema-optionalyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL like support with command line toolnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava plugins
Triggersnoyes, Notifications (with Streaming only)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infodynamic graph partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using RAFTyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infowith snapshot isolationoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyes infowith periodic snapshot and write-ahead logging (WAL) of changesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modeyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)Users, roles and permissionsyes
More information provided by the system vendor
Apache ImpalaBangdbMemgraphSolr
Specific characteristicsMemgraph directly connects to your streaming infrastructure so you and your team...
» more
Competitive advantagesBusiness Source License ensures a future for the Memgraph community MAGE algorithm...
» more
Typical application scenariosGraph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more
Licensing and pricing modelsYou can check out our pricing model and licenses on the company website .
» more

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Apache ImpalaBangdbMemgraphSolr
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