DBMS > Apache Phoenix vs. GridGain vs. LeanXcale vs. Sadas Engine

System Properties Comparison Apache Phoenix vs. GridGain vs. LeanXcale vs. Sadas Engine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

GridGain is an in-memory computing platform, built on Apache Ignite

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

Technical documentation

phoenix.apache.org

www.gridgain.com/docs/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

GridGain Systems, Inc.

LeanXcale

SADAS s.r.l.

Initial release

2014

2007

2015

2006

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

GridGain 8.5.1

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version available

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

Java

Java, C++, .Net

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

through Apache Derby

yes

APIs and other access methods

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

C
Java
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Security Hooks for custom implementations

Access rights for users, groups and roles according to SQL-standard

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

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

Deep dive into Azure HDInsight 4.0
25 September 2018, azure.microsoft.com

provided by Google News

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

GridGain's 2023 Growth Positions Company for Strong 2024
24 January 2024, PR Newswire

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

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

provided by Google News

Share this page