DBMS > Amazon Redshift vs. Badger vs. FileMaker vs. Hazelcast vs. TigerGraph

System Properties Comparison Amazon Redshift vs. Badger vs. FileMaker vs. Hazelcast vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

A widely adopted in-memory data grid

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

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

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

github.com/dgraph-io/badger

www.claris.com/filemaker

hazelcast.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

godoc.org/github.com/dgraph-io/badger

www.claris.com/resources/documentation

hazelcast.org/imdg/docs

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

DGraph Labs

Claris

a subsidiary of Apple

Hazelcast

Initial release

2012

2017

1983

2008

2017

Current release

19.4.1, November 2021

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

iOS

client part only
Linux
OS X
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

A http query request can return the data in XML format

yes

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

via plugins

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

PHP

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Event Listeners, Executor Services

yes

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

yes

none

Source-replica replication, warm standby

since Version 14

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts and connection to external directory services

Role-based access control

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