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DBMS > Google Cloud Spanner vs. Heroic vs. Ignite vs. Teradata Aster

System Properties Comparison Google Cloud Spanner vs. Heroic vs. Ignite vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHeroic  Xexclude from comparisonIgnite  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitecloud.google.com/­spannergithub.com/­spotify/­heroicignite.apache.org
Technical documentationcloud.google.com/­spanner/­docsspotify.github.io/­heroicapacheignite.readme.io/­docs
DeveloperGoogleSpotifyApache Software FoundationTeradata
Initial release2017201420152005
Current releaseApache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .Net
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesFlexible 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 dateyesyesyesyes
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.nonoyesyes infoin Aster File Store
Secondary indexesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)R packages
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yesyes (replicated cache)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 methodsyes infousing Google Cloud Dataflownoyes (compute grid and hadoop accelerator)yes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnoACIDACID
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerHeroicIgniteTeradata Aster
Recent citations in the news

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google Spanner: When Do You Need to Move to It?
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What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

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Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

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