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DBMS > Apache Impala vs. Datastax Enterprise vs. GigaSpaces vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Impala vs. Datastax Enterprise vs. GigaSpaces vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGlobally distributed, horizontally scalable, multi-model database service
Primary database modelRelational DBMSWide column storeDocument store
Object oriented DBMS infoValues are user defined objects
Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Graph DBMS
Search engine
Spatial 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
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websiteimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisewww.gigaspaces.comazure.microsoft.com/­services/­cosmos-db
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datastax.comdocs.gigaspaces.com/­latest/­landing.htmllearn.microsoft.com/­azure/­cosmos-db
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxGigaspaces TechnologiesMicrosoft
Initial release2013201120002014
Current release4.1.0, June 20226.8, April 202015.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageC++JavaJava, C++, .Net
Server operating systemsLinuxLinux
OS X
Linux
macOS
Solaris
Windows
hosted
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON types
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 infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyes infoAll properties auto-indexed by default
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLSQL-99 for query and DML statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesJavaScript
Triggersnoyesyes, event driven architectureJavaScript
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"ShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoMap-Reduce pattern can be built with XAP task executorswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
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 Consistency infoConsistency level configurable: ALL, QUORUM, ANYBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDMulti-item ACID transactions with snapshot isolation within a partition
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per objectRole-based access controlAccess rights can be defined down to the item level
More information provided by the system vendor
Apache ImpalaDatastax EnterpriseGigaSpacesMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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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More resources
Apache ImpalaDatastax EnterpriseGigaSpacesMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
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