DBMS > Heroic vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. VoltDB

System Properties Comparison Heroic vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. VoltDB

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

github.com/spotify/heroic

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/advantage-database-server.html

www.voltdb.com

Technical documentation

spotify.github.io/heroic

docs.keydb.dev

docs.microsoft.com/azure/synapse-analytics

docs.voltdb.com

Developer

Spotify

EQ Alpha Technology Ltd.

Microsoft

Sybase, SAP

VoltDB Inc.

Initial release

2014

2019

2016

1993

2010

Current release

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD-3

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

Linux

hosted

Linux
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

via Elasticsearch

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

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

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
Java
PHP

Delphi
Perl
PHP

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

Transact SQL

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

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

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Snapshots and command logging

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

simple password-based access control and ACL

yes

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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