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DBMS > AnzoGraph DB vs. Databricks vs. LevelDB vs. Sqrrl vs. Tkrzw

System Properties Comparison AnzoGraph DB vs. Databricks vs. LevelDB vs. Sqrrl vs. Tkrzw

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonSqrrl  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAdaptable, secure NoSQL built on Apache AccumuloA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Key-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecambridgesemantics.com/­anzographwww.databricks.comgithub.com/­google/­leveldbsqrrl.comdbmx.net/­tkrzw
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperCambridge SemanticsDatabricksGoogleAmazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release20182013201120122020
Current release2.3, January 20211.23, February 20210.9.3, August 2020
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialOpen Source infoBSDcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
LinuxLinux
macOS
Data schemeSchema-free and OWL/RDFS-schema supportFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesno
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.noyesnono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.with Databricks SQLnonono
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC++
Java
Python
Python
R
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
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions and aggregatesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryesnoneselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no
More information provided by the system vendor
AnzoGraph DBDatabricksLevelDBSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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AnzoGraph DBDatabricksLevelDBSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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