DBMS > BoltDB vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. RocksDB

System Properties Comparison BoltDB vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Primary database model

Key-value store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

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

Website

github.com/boltdb/bolt

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

azure.microsoft.com/services/synapse-analytics

rocksdb.org

Technical documentation

docs.heavy.ai

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

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

HEAVY.AI, Inc.

Google

Microsoft

Facebook, Inc.

Initial release

2013

2016

2014

2016

2013

Current release

5.10, January 2022

2.1.12, February 2017

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Open Source

BSD

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

C++ and CUDA

JavaScript

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

yes

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

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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