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DBMS > Aerospike vs. Google Cloud Spanner vs. Graphite vs. GridDB vs. SAP IQ

System Properties Comparison Aerospike vs. Google Cloud Spanner vs. Graphite vs. GridDB vs. SAP IQ

Editorial information provided by DB-Engines
NameAerospike infopreviously called Citrusleaf  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGraphite  Xexclude from comparisonGridDB  Xexclude from comparisonSAP IQ infoformer name: Sybase IQ  Xexclude from comparison
DescriptionFlash-optimized In-memory NoSQL DatabaseA 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.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperScalable in-memory time series database optimized for IoT and Big DataColumnar RDBMS optimized for Big Data analytics
Primary database modelDocument store
Graph DBMS infoleveraging Apache Tinkerpop
Key-value store
Spatial DBMS
Relational DBMSTime Series DBMSTime Series DBMSRelational DBMS infocolumn-oriented
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.78
Rank#61  Overall
#11  Document stores
#3  Graph DBMS
#7  Key-value stores
#2  Spatial DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.75
Rank#104  Overall
#53  Relational DBMS
Websiteaerospike.comcloud.google.com/­spannergithub.com/­graphite-project/­graphite-webgriddb.netwww.sap.com/­products/­technology-platform/­sybase-iq-big-data-management.html
Technical documentationdocs.aerospike.comcloud.google.com/­spanner/­docsgraphite.readthedocs.iodocs.griddb.nethelp.sap.com/­docs/­SAP_IQ
Social network pagesLinkedInTwitterFacebookYouTube
DeveloperAerospikeGoogleChris DavisToshiba CorporationSAP, formerly Sybase
Initial release20122017200620131994
Current release7.0, November 20235.1, August 202216.1 SPS04, April 2019
License infoCommercial or Open SourceOpen Source infoApache and AGPL Licenses; open sourced in June 2014; commercial Enterprise Edition availablecommercialOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCPythonC++
Server operating systemsLinuxhostedLinux
Unix
LinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJDBC
Proprietary protocol
TinkerPop Gremlin
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Sockets
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Erlang
Go
Java
JavaScript (Node.js)
Lua
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infowith Luanononoyes
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingshared disk or shared nothing architectures with SAP IQ Multiplexer
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.noneSource-replica replicationSAP/Sybase Replication Server
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoAerospike Aggregation Framework is similar to Map/Reduceyes infousing Google Cloud DataflownoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency in cross-datacenter configuration and Immediate Consistency in local cluster configurationImmediate ConsistencynoneImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of operationsACID infoStrict serializable isolationnoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infolockingyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and roles infowith Enterprise Edition onlyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Aerospike infopreviously called CitrusleafGoogle Cloud SpannerGraphiteGridDBSAP IQ infoformer name: Sybase IQ
Specific characteristicsAerospike is an enterprise-class, NoSQL database solution delivering predictable...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesOptimized for use with SSDs (solid-state hard drives) Scales horizontally and vertically...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosAerospike excels in mission-critical applications that have mixed read/write workloads...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersNielsen, Williams-Sonoma, Inmobi, AppNexus, Telco (confidential), Financial Services...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsAerospike's combination of speed, scalability, and reliability delivers 10x performance...
» more
GitHub trending repository
» more
Licensing and pricing modelsSubscription-based Enterprise Edition and free, open-source Community Edition
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
News

New Aerospike Release Lets Enterprises Consolidate Expensive Legacy Cache And Database Platforms
15 May 2024

Aerospike Recognized by Independent Research Firm Among Notable Vendors in Vector Databases Report
7 May 2024

Aerospike Closes $109M in Growth Capital from Sumeru Equity Partners
4 April 2024

Aerospike Achieves the new AWS Advertising and Marketing Technology Competency
30 November 2023

Aerospike Showcases New Levels of Database Performance, Price, and Sustainability on Graviton3 at AWS re:Invent
28 November 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Aerospike infopreviously called CitrusleafGoogle Cloud SpannerGraphiteGridDBSAP IQ infoformer name: Sybase IQ
DB-Engines blog posts

Evaluating Hbase and Aerospike Solutions for Real-time System of Record
17 March 2020,  Srini Srinivasan, Aerospike (sponsor) 

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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