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DBMS > BigObject vs. GeoSpock vs. Netezza vs. TimescaleDB

System Properties Comparison BigObject vs. GeoSpock vs. Netezza vs. TimescaleDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGeoSpock  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTimescaleDB  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for real-time computations and queriesSpatial and temporal data processing engine for extreme data scaleData warehouse and analytics appliance part of IBM PureSystemsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitebigobject.iogeospock.comwww.ibm.com/­products/­netezzawww.timescale.com
Technical documentationdocs.bigobject.iodocs.timescale.com
DeveloperBigObject, Inc.GeoSpockIBMTimescale
Initial release201520002017
Current release2.0, September 20192.15.0, May 2024
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialOpen Source infoApache 2.0
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 languageJava, JavascriptC
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux infoincluded in applianceLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyestemporal, categoricalyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for query only (using Presto)yesyes infofull PostgreSQL SQL syntax
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresLuanoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnono
User concepts infoAccess controlnoAccess rights for users can be defined per tableUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
BigObjectGeoSpockNetezza infoAlso called PureData System for Analytics by IBMTimescaleDB
Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

GeoSpock launches pioneering new spatial Big Data platform
27 February 2019, Geospatial World

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

Netezza Performance Server
12 August 2020, ibm.com

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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