DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > GridGain vs. IBM Db2 Event Store vs. Spark SQL vs. TinkerGraph

System Properties Comparison GridGain vs. IBM Db2 Event Store vs. Spark SQL vs. TinkerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use casesSpark SQL is a component on top of 'Spark Core' for structured data processingA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelKey-value store
Relational DBMS
Event Store
Time Series DBMS
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitewww.gridgain.comwww.ibm.com/­products/­db2-event-storespark.apache.org/­sqltinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGridGain Systems, Inc.IBMApache Software Foundation
Initial release2007201720142009
Current releaseGridGain 8.5.12.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC and C++ScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeyesyesyesschema-free
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.yesnonono
Secondary indexesyesnonono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Python
R
Scala
Groovy
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yesnono
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Active-active shard replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistencynone
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesno
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardnono

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
GridGainIBM Db2 Event StoreSpark SQLTinkerGraph
Recent citations in the news

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & Files

GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

GridGain to Sponsor and Speak at Three Key Industry Events in May 2024
2 May 2024, PR Newswire

GridGain Adds Andy Sacks as Chief Revenue Officer, Promotes Lalit Ahuja to Chief Customer and Product Officer ...
17 July 2023, Yahoo Finance

GridGain — Extreme Speed and Scale for Data-Intensive Apps
21 September 2014, gridgain.com

provided by Google News

The vision for Db2
26 February 2019, biplatform.nl

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Feature Engineering for Time-Series Using PySpark on Databricks
15 May 2024, Towards Data Science

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

Automated testing of Amazon Neptune data access with Apache TinkerPop Gremlin | Amazon Web Services
28 September 2022, AWS Blog

Simple Deployment of a Graph Database: JanusGraph | by Edward Elson Kosasih
12 October 2020, Towards Data Science

Why developers like Apache TinkerPop, an open source framework for graph computing | Amazon Web Services
27 September 2021, AWS Blog

InfiniteGraph Gets Support for Common Graph Database Language and More
21 February 2012, SiliconANGLE News

Introducing Gremlin query hints for Amazon Neptune | AWS Database Blog
26 February 2019, AWS Blog

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here