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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Drizzle vs. Ehcache vs. Google Cloud Datastore

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Drizzle vs. Ehcache vs. Google Cloud Datastore

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDrizzle  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely adopted Java cache with tiered storage optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSKey-value storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.ehcache.orgcloud.google.com/­datastore
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ehcache.org/­documentationcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsDrizzle project, originally started by Brian AkerTerracotta Inc, owned by Software AGGoogle
Initial release20132016200820092008
Current release4.1.0, June 202217037.2.4, September 20123.10.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++Java
Server operating systemsLinuxLinuxFreeBSD
Linux
OS X
All OS with a Java VMhosted
Data schemeyesSchema and schema-less with LDAP viewsyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptionalyesyesyes, details here
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.noyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensionsnoSQL-like query language (GQL)
APIs and other access methodsJDBC
ODBC
LDAPJDBCJCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C++
Java
PHP
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononousing Google App Engine
Triggersnoyesno infohooks for callbacks inside the server can be used.yes infoCache Event ListenersCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
Source-replica replication
yes infoby using Terracotta ServerMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationTunable Consistency (Strong, Eventual, Weak)Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynonoyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDyes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache ImpalaAtos Standard Common RepositoryDrizzleEhcacheGoogle Cloud Datastore
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