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DBMS > Apache Impala vs. BigchainDB vs. Datastax Enterprise vs. Sphinx

System Properties Comparison Apache Impala vs. BigchainDB vs. Datastax Enterprise vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigchainDB  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDataStax 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.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeWide column storeSearch engine
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
Score0.85
Rank#208  Overall
#35  Document stores
Score5.93
Rank#56  Overall
#4  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteimpala.apache.orgwww.bigchaindb.comwww.datastax.com/­products/­datastax-enterprisesphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlbigchaindb.readthedocs.io/­en/­latestdocs.datastax.comsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxSphinx Technologies Inc.
Initial release2013201620112001
Current release4.1.0, June 20226.8, April 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL v3commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++PythonJavaC++
Server operating systemsLinuxLinuxLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesno
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.nonono
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
CLI Client
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCGo
Haskell
Java
JavaScript
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess rights for users can be defined per objectno
More information provided by the system vendor
Apache ImpalaBigchainDBDatastax EnterpriseSphinx
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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Apache ImpalaBigchainDBDatastax EnterpriseSphinx
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