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DBMS > Apache Impala vs. Datastax Enterprise vs. EsgynDB vs. IRONdb vs. Valentina Server

System Properties Comparison Apache Impala vs. Datastax Enterprise vs. EsgynDB vs. IRONdb vs. Valentina Server

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonEsgynDB  Xexclude from comparisonIRONdb  Xexclude from comparisonValentina Server  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopDataStax 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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityObject-relational database and reports server
Primary database modelRelational DBMSWide column storeRelational DBMSTime Series DBMSRelational 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score5.80
Rank#60  Overall
#4  Wide column stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisewww.esgyn.cnwww.circonus.com/solutions/time-series-database/www.valentina-db.net
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datastax.comdocs.circonus.com/irondb/category/getting-startedvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxEsgynCirconus LLC.Paradigma Software
Initial release20132011201520171999
Current release4.1.0, June 20226.8, April 2020V0.10.20, January 20185.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageC++JavaC++, JavaC and C++
Server operating systemsLinuxLinux
OS X
LinuxLinuxLinux
OS X
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histogramsyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
ADO.NET
JDBC
ODBC
HTTP APIODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Proceduresyes, in Luayes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"ShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingMulti-source replication between multi datacentersconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per objectfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDatastax EnterpriseEsgynDBIRONdbValentina Server
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 ImpalaDatastax EnterpriseEsgynDBIRONdbValentina Server
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