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DBMS > Apache Impala vs. Badger vs. Datastax Enterprise vs. Quasardb

System Properties Comparison Apache Impala vs. Badger vs. Datastax Enterprise vs. Quasardb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Distributed, high-performance timeseries database
Primary database modelRelational DBMSKey-value storeWide column storeTime Series DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score5.93
Rank#56  Overall
#4  Wide column stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerwww.datastax.com/­products/­datastax-enterprisequasar.ai
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datastax.comdoc.quasar.ai/­master
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsDataStaxquasardb
Initial release2013201720112009
Current release4.1.0, June 20226.8, April 20203.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoJavaC++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
OS X
BSD
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infointeger and binary
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 indexesyesnoyesyes infowith tags
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query language
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infono "single point of failure"Sharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneconfigurable replication factor, datacenter aware, advanced replication for edge computingSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyeswith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users can be defined per objectCryptographically strong user authentication and audit trail
More information provided by the system vendor
Apache ImpalaBadgerDatastax EnterpriseQuasardb
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Apache ImpalaBadgerDatastax EnterpriseQuasardb
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