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DBMS > Badger vs. HEAVY.AI vs. Ignite vs. LevelDB vs. Sqrrl

System Properties Comparison Badger vs. HEAVY.AI vs. Ignite vs. LevelDB vs. Sqrrl

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIgnite  Xexclude from comparisonLevelDB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Key-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Websitegithub.com/­dgraph-io/­badgergithub.com/­heavyai/­heavydb
www.heavy.ai
ignite.apache.orggithub.com/­google/­leveldbsqrrl.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.heavy.aiapacheignite.readme.io/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDGraph LabsHEAVY.AI, Inc.Apache Software FoundationGoogleAmazon infooriginally Sqrrl Data, Inc.
Initial release20172016201520112012
Current release5.10, January 2022Apache Ignite 2.61.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++ and CUDAC++, Java, .NetC++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Solaris
Windows
Illumos
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesno
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLnoyesANSI-99 for query and DML statements, subset of DDLnono
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGoAll languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)nono
Triggersnonoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoRound robinShardingnoneSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyes (replicated cache)noneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardSecurity Hooks for custom implementationsnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
BadgerHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IgniteLevelDBSqrrl
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