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DBMS > Ehcache vs. GeoSpock vs. Tarantool vs. Teradata Aster

System Properties Comparison Ehcache vs. GeoSpock vs. Tarantool vs. Teradata Aster

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGeoSpock  Xexclude from comparisonTarantool  Xexclude from comparisonTeradata Aster  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA widely adopted Java cache with tiered storage optionsSpatial and temporal data processing engine for extreme data scaleIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeRelational DBMSDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.ehcache.orggeospock.comwww.tarantool.io
Technical documentationwww.ehcache.org/­documentationwww.tarantool.io/­en/­doc
DeveloperTerracotta Inc, owned by Software AGGeoSpockVKTeradata
Initial release200920082005
Current release3.10.0, March 20222.0, September 20192.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, JavascriptC and C++
Server operating systemsAll OS with a Java VMhostedBSD
Linux
macOS
Linux
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.nononoyes infoin Aster File Store
Secondary indexesnotemporal, categoricalyesyes
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)Full-featured ANSI SQL supportyes
APIs and other access methodsJCacheJDBCOpen binary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJavaC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresR packages
Triggersyes infoCache Event Listenersnoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerAutomatic shardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlnoAccess rights for users can be defined per tableAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
EhcacheGeoSpockTarantoolTeradata Aster
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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