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DBMS > Apache Impala vs. Badger vs. Bangdb vs. Elasticsearch vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Impala vs. Badger vs. Bangdb vs. Elasticsearch vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonBangdb  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Converged 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 metricElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSKey-value storeDocument store
Graph DBMS
Time Series DBMS
Search engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMSDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerbangdb.comwww.elastic.co/­elasticsearchazure.microsoft.com/­services/­synapse-analytics
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.bangdb.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsSachin Sinha, BangDBElasticMicrosoft
Initial release20132017201220102016
Current release4.1.0, June 2022BangDB 2.0, October 20218.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoBSD 3Open Source infoElastic Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC, C++JavaC++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxAll OS with a Java VMhosted
Data schemeyesschema-freeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesnoyes: string, long, double, int, geospatial, stream, eventsyesyes
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.nonononono
Secondary indexesyesnoyes infosecondary, composite, nested, reverse, geospatialyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL like support with command line toolSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C#
C++
Java
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Java
PHP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesTransact SQL
Triggersnonoyes, Notifications (with Streaming only)yes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factor, Knob for CAP (enterprise version only)yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneTunable 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
Foreign keys infoReferential integritynonononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, run db with in-memory only modeMemcached and Redis integration
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnoyes (enterprise version only)yes

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More resources
Apache ImpalaBadgerBangdbElasticsearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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