DBMS > Apache Impala vs. Ehcache vs. eXtremeDB
System Properties Comparison Apache Impala vs. Ehcache vs. eXtremeDB
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|Editorial information provided by DB-Engines
|Apache Impala Xexclude from comparison
|Ehcache Xexclude from comparison
|eXtremeDB Xexclude from comparison
|Analytic DBMS for Hadoop
|A widely adopted Java cache with tiered storage options
|Natively in-memory DBMS with options for persistency, high-availability and clustering
|Primary database model
Time Series DBMS
|Secondary database models
|Apache Software Foundation Apache top-level project, originally developed by Cloudera
|Terracotta Inc, owned by Software AG
|4.1.0, June 2022
|3.10.0, March 2022
|License Commercial or Open Source
|Open Source Apache Version 2
|Open Source Apache Version 2; commercial licenses available
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
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|C and C++
|Server operating systems
|All OS with a Java VM
|Typing predefined data types such as float or date
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.
|no support of XML interfaces available
|SQL Support of SQL
|SQL-like DML and DDL statements
|yes with the option: eXtremeSQL
|APIs and other access methods
|.NET Client API
RESTful HTTP API
|Supported programming languages
|All languages supporting JDBC/ODBC
|Server-side scripts Stored procedures
|yes user defined functions and integration of map-reduce
|yes Cache Event Listeners
|yes by defining events
|Partitioning methods Methods for storing different data on different nodes
|Sharding by using Terracotta Server
|horizontal partitioning / sharding
|Replication methods Methods for redundantly storing data on multiple nodes
|selectable replication factor
|yes by using Terracotta Server
|Active Replication Fabric™ for IoT
Multi-source replication by means of eXtremeDB Cluster option
Source-replica replication by means of eXtremeDB High Availability option
|MapReduce Offers an API for user-defined Map/Reduce methods
|yes query execution via MapReduce
|Consistency concepts Methods to ensure consistency in a distributed system
|Tunable Consistency (Strong, Eventual, Weak)
|Foreign keys Referential integrity
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|yes supports JTA and can work as an XA resource
|Concurrency Support for concurrent manipulation of data
|yes Optimistic (MVCC) and pessimistic (locking) strategies available
|Durability Support for making data persistent
|yes using a tiered cache-storage approach
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|Access rights for users, groups and roles based on Apache Sentry and Kerberos
|More information provided by the system vendor
|eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
|eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
|Typical application scenarios
|IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
|Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
|With hundreds of customers and over 30 million devices/applications using the product...
|Licensing and pricing models
|For server use cases, there is a simple per-server license irrespective of the number...
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