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DBMS > Apache Impala vs. Datastax Enterprise vs. EsgynDB vs. GigaSpaces

System Properties Comparison Apache Impala vs. Datastax Enterprise vs. EsgynDB vs. GigaSpaces

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonEsgynDB  Xexclude from comparisonGigaSpaces  Xexclude from comparison
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 TrafodionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions
Primary database modelRelational DBMSWide column storeRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Graph DBMS
Search engine
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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Websiteimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisewww.esgyn.cnwww.gigaspaces.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datastax.comdocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxEsgynGigaspaces Technologies
Initial release2013201120152000
Current release4.1.0, June 20226.8, April 202015.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2; Commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++, JavaJava, C++, .Net
Server operating systemsLinuxLinux
OS X
LinuxLinux
macOS
Solaris
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLyesSQL-99 for query and DML statements
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
ADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
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++
Java
Python
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Proceduresyes
Triggersnoyesnoyes, event driven architecture
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"ShardingSharding
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 datacentersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesyes infoMap-Reduce pattern can be built with XAP task executors
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 infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
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-standardRole-based access control
More information provided by the system vendor
Apache ImpalaDatastax EnterpriseEsgynDBGigaSpaces
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...
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Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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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 EnterpriseEsgynDBGigaSpaces
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