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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonBangdb  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRiak KV  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 graphElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerDistributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value storeDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument storeSpatial 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
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerbangdb.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.bangdb.comdocs.microsoft.com/­azure/­synapse-analyticswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsSachin Sinha, BangDBMicrosoftOpenSource, formerly Basho Technologies
Initial release20132017201220162009
Current release4.1.0, June 2022BangDB 2.0, October 20213.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoBSD 3commercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC, C++C++Erlang
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
LinuxhostedLinux
OS X
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyes: string, long, double, int, geospatial, stream, eventsyesno
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, geospatialyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL like support with command line toolyesno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C#
C++
Java
Python
C#
Java
PHP
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoTransact SQLErlang
Triggersnonoyes, Notifications (with Streaming only)noyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding, horizontal partitioningSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factor, Knob for CAP (enterprise version only)yesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
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 mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnoyes (enterprise version only)yesyes, using Riak Security

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More resources
Apache ImpalaBadgerBangdbMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRiak KV
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