DBMS > GridGain vs. InfluxDB vs. Lovefield vs. RocksDB vs. StarRocks

System Properties Comparison GridGain vs. InfluxDB vs. Lovefield vs. RocksDB vs. StarRocks

Editorial information provided by DB-Engines

Name

Description

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

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

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

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

www.gridgain.com

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

rocksdb.org

www.starrocks.io

Technical documentation

www.gridgain.com/docs/index.html

docs.influxdata.com/influxdb

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/facebook/rocksdb/wiki

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

GridGain Systems, Inc.

Google

Facebook, Inc.

The Linux Foundation

since Feb 2023

Initial release

2007

2013

2014

2013

2020

Current release

GridGain 8.5.1

2.7.6, April 2024

2.1.12, February 2017

9.2.1, May 2024

3.3, June 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

BSD

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

Java, C++, .Net

JavaScript

C++

C++, Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

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

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

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

HTTP API
JSON over UDP

C++ API
Java API

JDBC
MySQL protocol

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

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Java

Server-side scripts

Stored procedures

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

user defined functions

Triggers

yes (cache interceptors and events)

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

horizontal partitioning

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

in enterprise version only

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

Security Hooks for custom implementations

simple rights management via user accounts

Role based access control and fine grained access rights

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