DBMS > Hazelcast vs. Heroic vs. PostGIS vs. RocksDB vs. SingleStore

System Properties Comparison Hazelcast vs. Heroic vs. PostGIS vs. RocksDB vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

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

Spatial extension of PostgreSQL

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

hazelcast.com

github.com/spotify/heroic

postgis.net

rocksdb.org

www.singlestore.com

Technical documentation

hazelcast.org/imdg/docs

spotify.github.io/heroic

postgis.net/documentation

github.com/facebook/rocksdb/wiki

docs.singlestore.com

Developer

Hazelcast

Spotify

Facebook, Inc.

SingleStore Inc.

Initial release

2008

2014

2005

2013

Current release

5.3.6, November 2023

3.4.2, February 2024

8.11.4, April 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

BSD

commercial

free developer edition 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++

C++, Go

Server operating systems

All OS with a Java VM

Linux

64 bit version required

Data scheme

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

but no triggers and foreign keys

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

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

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

based on PostgreSQL

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

yes

based on PostgreSQL

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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