DBMS > Apache Impala vs. H2GIS vs. Hazelcast vs. Tigris

System Properties Comparison Apache Impala vs. H2GIS vs. Hazelcast vs. Tigris

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Spatial extension of H2

A widely adopted in-memory data grid

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Document store

Relational DBMS

Document store

JSON support with IMDG 3.12

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

hazelcast.org/imdg/docs

www.tigrisdata.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

Hazelcast

Tigris Data, Inc.

Initial release

2013

2008

2022

Current release

4.1.0, June 2022

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

yes

Replicated Map

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

Role-based access control

Access rights for users and roles

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

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast appoints Anthony Griffin as Chief Architect -
11 June 2024, Enterprise Times

Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit
15 May 2024, Datanami

Real-Time Data Platform Hazelcast Introduces New Chief Technology Officer Adrian Soars
7 November 2023, Finovate

provided by Google News

Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

FerretDB Provides Alternative to MongoDB
19 May 2023, Datanami

Latest Asigra platform targets SaaS backup for MSPs
6 March 2023, TechTarget

provided by Google News

Share this page