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DBMS > LevelDB vs. PostGIS vs. SQream DB vs. Vertica

System Properties Comparison LevelDB vs. PostGIS vs. SQream DB vs. Vertica

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonPostGIS  Xexclude from comparisonSQream DB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpatial extension of PostgreSQLa GPU-based, columnar RDBMS for big data analytics workloadsCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeSpatial DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.35
Rank#111  Overall
#19  Key-value stores
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­google/­leveldbpostgis.netsqream.comwww.vertica.com
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdpostgis.net/­documentationdocs.sqream.comvertica.com/­documentation
DeveloperGoogleSQream TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2011200520172005
Current release1.23, February 20213.4.2, February 20242022.1.6, December 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoGPL v2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsIllumos
Linux
OS X
Windows
LinuxLinux
Data schemeschema-freeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyesyes, ANSI Standard SQL Typesyes
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.noyesno
Secondary indexesnoyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functionsuser defined functions in Pythonyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneyes infobased on PostgreSQLhorizontal and vertical partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infobased on PostgreSQLnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes infobased on PostgreSQLfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
LevelDBPostGISSQream DBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
LevelDBPostGISSQream DBVertica infoOpenText™ Vertica™
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