DBMS > Apache Impala vs. GridGain vs. Heroic vs. SAP Advantage Database Server vs. Tkrzw

System Properties Comparison Apache Impala vs. GridGain vs. Heroic vs. SAP Advantage Database Server vs. Tkrzw

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Low-cost RDBMS with access to ISAM and FoxPro data structures

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

impala.apache.org

www.gridgain.com

github.com/spotify/heroic

www.sap.com/products/advantage-database-server.html

dbmx.net/tkrzw

Technical documentation

impala.apache.org/impala-docs.html

www.gridgain.com/docs/index.html

spotify.github.io/heroic

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

GridGain Systems, Inc.

Spotify

Sybase, SAP

Mikio Hirabayashi

Initial release

2013

2007

2014

1993

2020

Current release

4.1.0, June 2022

GridGain 8.5.1

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

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, C++, .Net

Java

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

APIs and other access methods

JDBC
ODBC

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

Delphi
Perl
PHP

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate 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

caching of (temporary) tables can be configured

yes

using specific database classes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

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