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DBMS > Apache Impala vs. Badger vs. Datastax Enterprise vs. SAP HANA vs. Yaacomo

System Properties Comparison Apache Impala vs. Badger vs. Datastax Enterprise vs. SAP HANA vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonSAP HANA  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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.In-memory, column based data store. Available as appliance or cloud serviceOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial 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
Score5.80
Rank#60  Overall
#4  Wide column stores
Score44.69
Rank#22  Overall
#16  Relational DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerwww.datastax.com/­products/­datastax-enterprisewww.sap.com/­products/­hana.htmlyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datastax.comhelp.sap.com/­hana
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsDataStaxSAPQ2WEB GmbH
Initial release20132017201120102009
Current release4.1.0, June 20226.8, April 20202.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono infoalso available as a cloud based serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageC++GoJava
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Appliance or cloud-serviceAndroid
Linux
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements (CQL); Spark SQLyesyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGoC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoSQLScript, R
Triggersnonoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infono "single point of failure"yeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneconfigurable replication factor, datacenter aware, advanced replication for edge computingyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users can be defined per objectyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaBadgerDatastax EnterpriseSAP HANAYaacomo
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 EnterpriseSAP HANAYaacomo
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