DBMS > GridGain vs. Heroic vs. InfluxDB vs. SAP IQ vs. SQLite

System Properties Comparison GridGain vs. Heroic vs. InfluxDB vs. SAP IQ vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

DBMS for storing time series, events and metrics

Columnar RDBMS optimized for Big Data analytics

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.gridgain.com

github.com/spotify/heroic

www.influxdata.com/products/influxdb-overview

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.sqlite.org

Technical documentation

www.gridgain.com/docs/index.html

spotify.github.io/heroic

docs.influxdata.com/influxdb

help.sap.com/docs/SAP_IQ

www.sqlite.org/docs.html

Developer

GridGain Systems, Inc.

Spotify

SAP, formerly Sybase

Dwayne Richard Hipp

Initial release

2007

2014

2013

1994

2000

Current release

GridGain 8.5.1

2.7.6, April 2024

16.1 SPS04, April 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Public Domain

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, C++, .Net

Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

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

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

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

HTTP API
JSON over UDP

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

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

in enterprise version only

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

selectable replication factor

in enterprise version only

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

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

Depending on used storage engine

yes

User concepts

Access control

Security Hooks for custom implementations

simple rights management via user accounts

fine grained access rights according to SQL-standard

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