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DBMS > GigaSpaces vs. Hypertable vs. Sqrrl vs. Teradata Aster

System Properties Comparison GigaSpaces vs. Hypertable vs. Sqrrl vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHypertable  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAn open source BigTable implementation based on distributed file systems such as HadoopAdaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Wide column storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Websitewww.gigaspaces.comsqrrl.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.html
DeveloperGigaspaces TechnologiesHypertable Inc.Amazon infooriginally Sqrrl Data, Inc.Teradata
Initial release2000200920122005
Current release15.5, September 20200.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++Java
Server operating systemsLinux
macOS
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Data schemeschema-freeschema-freeschema-freeFlexible 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 dateyesnoyesyes
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.no infoXML can be used for describing objects metadatayes infoin Aster File Store
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsnonoyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
C++ API
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C++
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnonoR packages
Triggersyes, event driven architecturenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
selectable replication factor on file system levelselectable replication factor infomaking use of Hadoopyes 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 methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic updates per row, document, or graph entityACID
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.yesno
User concepts infoAccess controlRole-based access controlnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
GigaSpacesHypertableSqrrlTeradata Aster
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