DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Pinot vs. eXtremeDB vs. GridGain vs. TigerGraph

System Properties Comparison Apache Pinot vs. eXtremeDB vs. GridGain vs. TigerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGridGain  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyNatively in-memory DBMS with options for persistency, high-availability and clusteringGridGain is an in-memory computing platform, built on Apache IgniteA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score0.79
Rank#212  Overall
#100  Relational DBMS
#18  Time Series DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websitepinot.apache.orgwww.mcobject.comwww.gridgain.comwww.tigergraph.com
Technical documentationdocs.pinot.apache.orgwww.mcobject.com/­docs/­extremedb.htmwww.gridgain.com/­docs/­index.htmldocs.tigergraph.com
DeveloperApache Software Foundation and contributorsMcObjectGridGain Systems, Inc.
Initial release2015200120072017
Current release1.0.0, September 20238.2, 2021GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial, open sourcecommercial
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 languageJavaC and C++Java, C++, .Net, Python, REST, SQLC++
Server operating systemsAll OS with a Java JDK11 or higherAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
z/OS
Linux
Data schemeyesyesyesyes
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.no infosupport of XML interfaces availableyesno
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith the option: eXtremeSQLANSI-99 for query and DML statements, subset of DDLSQL-like query language (GSQL)
APIs and other access methodsJDBC.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)yes
Triggersyes infoby defining eventsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
Role-based access control

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
Apache PinoteXtremeDBGridGainTigerGraph
Recent citations in the news

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

Pinot for Low-Latency Offline Table Analytics
29 August 2024, Uber

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

StarTree Makes Observability Case for Apache Pinot Database
8 May 2024, DevOps.com

provided by Google News

McObject
17 November 2021, Electronic Design

McObject Collaborates with Wind River to Deliver First-Ever
14 September 2021, GlobeNewswire

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject and GoldenSource Collaborate on Regtech EDM Offering
28 June 2017, Financial IT

provided by Google News

GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideBIGDATA

GridGain Sponsoring Strategic AI and Kafka Conferences This Month
4 September 2024, Datanami

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

Data Management News for the Week of July 12; Updates from Cloudera, HerculesAI, Oracle & More
12 July 2024, Solutions Review

Lalit Ahuja
13 August 2024, Forbes

provided by Google News

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

TigerGraph raises $105M Series C for its enterprise graph database
17 February 2021, TechCrunch

provided by Google News



Share this page

Featured Products

Milvus logo

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

RaimaDB logo

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

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

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Neo4j logo

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

Present your product here