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DBMS > GigaSpaces vs. GridDB vs. Sadas Engine vs. TimescaleDB vs. Vertica

System Properties Comparison GigaSpaces vs. GridDB vs. Sadas Engine vs. TimescaleDB vs. Vertica

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or on-premises analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#175  Overall
#30  Document stores
#6  Object oriented DBMS
Score1.23
Rank#159  Overall
#11  Time Series DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Score4.70
Rank#83  Overall
#5  Time Series DBMS
Score19.29
Rank#38  Overall
#24  Relational DBMS
Websitewww.gigaspaces.comgriddb.netwww.sadasengine.comwww.timescale.comwww.vertica.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbdocs.timescale.comvertica.com/­documentation
DeveloperGigaspaces TechnologiesToshiba CorporationSADAS s.r.l.TimescaleMicro Focus infoprior to that Hewlett Packard
Initial release20002013200620172005
Current release15.5, September 20204.6, February 20218.02.6.0, February 202211.1, February 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree trial version availableOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageJava, C++, .NetC++C++CC++
Server operating systemsLinux
macOS
Solaris
Windows
LinuxAIX
Linux
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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 metadatanonoyesno
Secondary indexesyesyesyesyesNo Indexes Required
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)yesyes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Proprietary protocolJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes, event driven architectureyesnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationnoneSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyesyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlRole-based access controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GigaSpacesGridDBSadas EngineTimescaleDBVertica infoVertica Analytics Platform
Specific characteristicsGigaSpaces, the pioneer of In-Memory Computing , drives enterprise digital transformation...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Timescale is the creator of TimescaleDB , the first open-source relational database...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantages​ AI Driven Autonomous Operations – GigaSpaces’ unique AI driven technology simplifies...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosApplication Acceleration, Smart Caching, BI Acceleration on Fresh Data, Digital Integration...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Time-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersMorgan Stanley, Bank of America, Goldman Sachs, PriceRunner, Cerner, Societe Generale,...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsForrester has positioned GigaSpaces as a strong performer in The Forrester Wave™:...
» more
GitHub trending repository
» more
With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
» more
Licensing and pricing modelsGigaSpaces offers both open source and commercial editions with annual subscriptions....
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
TimescaleDB is available as a self-hosted product under two licenses, the Timescale...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
GigaSpacesGridDBSadas EngineTimescaleDBVertica infoVertica Analytics Platform
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